HGS MathComp Curriculum & Events

Teaching methods:

The course is divided into six blocks (half days). Each block will consist of a mixture of presentations and hands-on exercises. In the presentations we take starting point in real-world datasets and scientific problems and discuss the relevant statistical methods. Focus is on the link between data and methods, implementation, and interpretation of results. Exercises will be practical, with exploration and analysis of real-world datasets. Participants are expected to use the statistical software environments R and RStudio for the exercises.

Teaching material:

The teachers will provide slides, programs/output from R Markdown, data, and exercises. Apart from this, notice that the book R for Data Science (https://r4ds.had.co.nz or https://r4ds.hadley.nz) is useful for data manipulation and visualization.

Tentative plan:

Each block (A-F) is expected to last for a morning/afternoon.

A. Recap (getting a common language)

• Basic statistical principles (data types, random variation, estimation, hypothesis tests, etc.)
• Workflow with R Markdown

B. Models for continuous outcomes

• Models for regression, ANOVA, clustered/blocked data (linear mixed models)
• Model diagrams
• Hypothesis tests for overall effects in regression, ANOVA, linear mixed models

C. Elaborate analysis of data with continuous outcome

• Estimated marginal means (emmeans)
• Pairwise comparisons and adjustment for multiple testing
• Statistical power

D. Modifications of models and analyses for continuous outcomes

• Model validation and data transformation
• Bootstrap computation of standard errors and p-values

E. Models with non-linear relationships

• Additive models (GAMs)
• Non-linear regression

F. Prediction with multiple/many covariates

• Preprocessing
• Training/validation/testing
• Regression-based models for prediction
• Principal component analysis (PCA)

This second seminar is planned as follow-up session to the Introduction seminar for those researchers who would like to review their own work in terms of potential patent protection. For that purpose, participants of the Introduction seminar will be asked to provide a short summary of their own already-disclosed innovations. Three to four selected cases will be analyzed and discussed with all participants with regard to the patentability requirements.
Concerning the patentability of not-yet-disclosed innovations, at the end of the workshop there will be the possibility to plan specific one-to-one meetings to avoid compromising the novelty of the underlying subject matter.

11:00 Antonia Papapostolou (Supervisor A. Dreuw)
“Development of Quantum Chemical Methods for the Calculation of Molecular Response Properties”

11:20 Adrian Müller (Supervisor A. Dreuw)
“Quantum mechanical method development for MOST systems”

11:40 Friederike Schneider (Supervisor A. Dreuw)
"High-Performance Quantum Chemical Computing"

12:00 Panasun Manorost (Supervisor P. Bastian)
“Surface-subsurface flow simulation. Creating Method and Application”

12:20 Pascal Lafrenz (Supervisors H. Kaessmann, B. Velten)
"Multi-omics data integration and evolutionary models to understand de novo gene birth and human evolution"

14:00 Leonie Kreis (Supervisor R. Herzog)
„Multilevel architectures and algorithms in deep learning“

14:20 Yannick Pauler (Supervisor C. Rother)
“Recovering 3D Information from a Moving Camera"

14:40 Leo Nguyen (Supervisor U. Koethe)
„Advancing Lithium Battery Design through Machine Learning using Invertible Neural Networks“

This seminar illustrates the strategic relevance of patents in the field of software for academic institutions and explains the requirements for software-based innovation to be considered as patentable software inventions. In particular, a series of examples will demonstrate opportunities and pitfalls when protecting software-based innovation by means of patent applications. One goal of the seminar is to provide researchers with a tool which they can use for assessing their own research results with regard to the potential that the underlying innovation can be protected via a patent.

In the 21st century, society faces multiple and highly interwoven global health challenges, linked to accelerating climate change, antimicrobial resistance, food and water insecurity, and an increasing number of infectious diseases. Threatening convergence, these health issues call for more effective and sustainable solutions to ensure that the global population continues to thrive. Scientists and researchers can massively contribute to discovering, co-designing, and evaluating these solutions.

In this context, Nature-based Solutions (NbS), while not yet commonplace, are increasingly gaining recognition alongside more conventional engineering solutions and healthcare interventions. The concept of NbS describes the innovative use of existing knowledge about natural systems to assist society in effectively addressing contemporary environmental, social and economic challenges while simultaneously providing ecological and health benefits. These win-win NbS include the management, restoration and protection of ecosystems, strategies for climate adaptation and mitigation and the greening of infrastructure.

The Summer School will explore the innovative potential of NbS to tackle two pressing global health challenges – climate change and pandemic prevention, which are highly interconnected and provide opportunities to design, apply and evaluate a range of win-win NbS to inform future policies based on scientific evidence.

The guest speakers will share their expertise and experience with the participants and will collaboratively work together on a capstone project, relevant to the development and presentation of a research project on NbS to tackle climate change and pandemics.The Summer School will promote interdisciplinary thinking and will encourage participants to bring examples of NbS beyond these two challenges for discussion to consider how to develop NbS that address concrete challenges and implement solutions in very diverse settings. As a result, the Summer School will allow participants to further connect, interact, and build a worthwhile network of expertise on NbS.

Advanced statistical methods are rapidly impregnating many scientific fields, offering new perspectives on long-standing problems. In materials science, data-driven methods are already bearing fruit in various disciplines, such as hard condensed matter or inorganic chemistry, while comparatively little has happened in soft matter. I will describe how we use multiscale simulations to leverage data-driven methods in soft matter. We aim at establishing structure-property relationships for complex thermodynamic processes across the chemical space of small molecules. Akin to screening experiments, we devise a high-throughput coarse-grained simulation framework. Coarse-graining is an appealing screening strategy for two main reasons: it significantly reduces the size of chemical space and it can suggest a low-dimensional representation of the structure-property relationship. I will briefly mention a biological application of our methodology that led to the discovery of in vivo active compounds. Finally, I will mention a number of ways machine learning can help fulfill the promise of connecting models at different scales.

Biosketch:

Tristan Bereau is a computational physicist working at the interface between multiscale modeling and machine learning for soft matter and biomolecules. He earned a Ph.D. in Physics at Carnegie Mellon University. After a postdoc at the University of Basel, he led an Emmy Noether research group at the Max Planck Institute for Polymer Research. He then moved to the University of Amsterdam as an assistant professor in chemistry and computer science, followed by a role in Industry. Tristan serves on the editorial boards of the journals Machine Learning: Science & Technnology and Computational Science and Engineering. He is currently a professor at the Institute for Theoretical Physics at the University of Heidelberg.

Convolutional Neural Networks (CNN) are the current backbone of deep learning architectures in a wide range of applications which process array data, like 2D/3D images. Despite this overwhelming success of the application of CNNs in terms of qualitative (visual) results and classification test set accuracies, this talk will point out some servere inherent problems of CNNs regarding their insufficient signal processing capabilities.
While these “signal processing flaws” have been largely ignored as test accuracies on many problems have been increasing over many years, recent research showed that current models are highly vulnerable to even the slightest changes in input distributions. In our latest works [1-5], we showed that the missing “robustness” of CNNs is not only due to insufficient training data, but to a large extend is also caused by faulty operators and architectures which are failing to adhere to basic signal processing demands. The aim of this talk is to give an overview of the dominant problems in the context of image processing and analysis and discuss possible counter measures.

References:
[1] Durall, R., Keuper, M., & Keuper, J. (2020). Watch your up-convolution: Cnn based generative deep neural networks are failing to reproduce spectral distributions. CVPR 2020
[2] Grabinski, J., Keuper, J., & Keuper, M. (2022). Aliasing and adversarial robust generalization of CNNs. Machine Learning, 111(11), 3925-3951.
[3] Grabinski, J., Jung, S., Keuper, J., & Keuper, M. (2022). FrequencyLowCut Pooling--Plug & Play against Catastrophic Overfitting. ECCV 2022
[4] Grabinski, J., Gavrikov, P., Keuper, J., & Keuper, M. Robust Models are less Over-Confident. NeurIPS 2022
[5] Gavrikov, P., & Keuper, J. (2022). CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters. CVPR 2022 (oral)

In 2021 a long-term HPC infrastructure (“Nationales Hochleistungsrechnen”; NHR) has been established to further develop HPC capabilities, HPC expertise and training offerings at German universities. Nine NHR centers are now offering their compute services, support activities and training free of charge to researchers at all German universities. These centers coordinate their investments as well as application and support profiles within the NHR-Verein.
The presentation will introduce the structure of the NHR program, central NHR activities of the NHR-Verein and the structure of the application process. It will specially report on offerings and developments at the NHR center at Friedrich-Alexander-Universität Erlangen-Nürnberg (NHR@RFAU) which focuses on atomistic applications and node-level performance engineering.

This hands-on workshop provides an overview of the German research funding landscape and explains how to exploit funding opportunities at the postdoctoral stage for further career advancement. Selected EU programmes within the framework of Horizon Europe are also covered. Practice scenarios for different research settings help to understand how to select and approach individual funding programmes to establish yourself as a principal investigator and build your research capacity.

This highly interactive workshop employs theoretical input, plenary discussions, practice scenarios, individual and small group work, experience sharing, and expert advice.

The school spreads over five days with theory sessions in the morning and hands-on exercises in the afternoon. The list of topics covered includes:

- Numerical methods for quantum dynamics
- MCTDH theory
- Hands-on exercises with the Heidelberg MCTDH package
- Introduction to polyspherical coordinates
- Mode combinations and multilayer tree generation
- Potential energy operators in sum-of-products form
- MCTDH for bosons and fermions (MCTDH-X)
- Density matrix renormalization group (DMRG) through the lens of MCTDH
- DMRG in electronic and vibrational problems

In this workshop we will analyze examples of effective and ineffective texts aimed at communicating research to a general audience. We will share tips and tricks on effective science writing, and finally, work in groups on translating a technical paper or report into an effective text that addresses a general audience. Participants can send proposals of papers and reports drawn from their research area, to be worked on in the workshop by 4th June (email address: nm-gastprofessur@mk.uni-heidelberg.de)

Lab presentations:
Jan Budczies, Daniel Durstewitz, Carsten Rother

Science talks:
• Iordanis Ourailidis (Budczies lab): AI-based detection of tumor budding in head and neck cancer
• Florian Hess (Durstewitz lab): Learning generative models of dynamical systems from time series data
• Felix Draxler (Rother lab): Generative Models - Applications and Guarantees

Machine-learning, which can learn to predict given labeled data, bares many promises for medical applications. And yet, experience shows that predictors that looked promising most often fail to bring the expected medical benefits. One reason is that they are evaluated detached from actual usage and medical outcomes.
And yet, test runing predictive models on actual medical decisions can be costly and dangerous. How do we bridge the gap? By improving machine-learning model evaluation. First, the metrics used to measure prediction error must capture as well as possible the cost-benefit tradeoffs of the final usage. Second, the evaluation procedure must really put models to the test: on a representative data sample, and accounting for uncertainty in model evaluation.

Biosketch:

Gaël Varoquaux is a research director working on data science at Inria (French Computer Science National research) where he leads the Soda team on computational and statistical methods to understand health and society with data. Varoquaux is an expert in machine learning, with an eye on applications in health and social science. He develops tools to make machine learning easier, suited for real-life, messy data. He co-funded scikit-learn, one of the reference machine-learning toolboxes, and helped build various central tools for data analysis in Python. He currently develops data-intensive approaches for epidemiology and public health, and worked for 10 years on machine learning for brain function and mental health. Varoquaux has a PhD in quantum physics supervised by Alain Aspect and is a graduate from Ecole Normale Superieure, Paris.

This talk presents a feasible study of optimal control techniques for cardiac defibrillation based on the bidomain-bath equations posed on a rabbit ventricle geometry. The bidomain model consists of a system of elliptic partial differential equations coupled with a non-linear parabolic equation of reaction-diffusion type, where a set of ordinary differential equations describes the reaction term, modeling ionic transport. Since ODEs describe the ionic currents in the tissue, the PDE part dominates the solving effort. Thus, it is unclear if commonly used splitting methods can outperform a coupled approach by maintaining good accuracy. The results will be presented in the first part based on comparing the coupled solver approach with commonly used splitting schemes to solve more sophisticated physiological models. Consequently, the novel memory-efficient computational technique will be demonstrated to solve the coupled systems of equations. In the second part, the optimal control approach for successful cardiac defibrillation will be shown based on minimizing a properly chosen cost functional depending on the extracellular current as input at the boundary of the bidomain-bath domain.

Biosketch:

Nagaiah Chamakuri got his M.Tech at IIT Madras, India, in 2002 and obtained his Ph.D. from Otto-von-Guericke University in 2007. After that, he worked as a Postdoc at several places in Austria and Germany. He worked as an Associate Professor at Mahindra-Ecole Centrale, Hyderabad from 2016-2019. Since 2020, he has been working as a faculty at the Indian Institute of Science Education and Research (IISER), Thiruvananthapuram, India. His scientific interests include the numerical solution of partial differential equations, Optimal control of PDEs, applications in fluid flow, Computational biology, and High-performance computing.

The human brain is one of the most complex and fascinating structures. It is still far from understood and therefore considered one the last biological frontiers. Its function is the result of intricate signal transmission networks and reactions occurring within and between neurons. To model and simulate such complexity, multiscale models are required that are aimed at reproducing brain function through a bottom-up approach, from the molecular to the whole brain level. This workshop will provide training in some of the computational tools developed in the Human Brain Project that enable brain simulation and modelling at the molecular and subcellular levels. This workshop is intended to offer an overview of these tools and their application and provide students and young researchers with the necessary theoretical background and practical experience to enable them to apply them in their own research. There will be a mix of lectures and practical session as well as discussions of case studies and the participants' own research problems.

In the early 1800s, Thomas Young performed a homespun experiment with a sunbeam split into two, and challenged our understanding of the nature of light. With the birth of quantum mechanics, starting in the early 1900s, this "double-slit" experiment—now done with individual particles—started challenging our ideas about the nature of reality. How can a single particle behave both like a particle and a wave? Does a particle, or indeed reality, exist before we look at it, or does looking create reality? Is there a place where the quantum world ends and the familiar classical world of our daily lives begins, and if so, can we find it? In the 1960s, Richard Feynman said that the deceptively simple double-slit experiment contains the "central mystery" of the quantum world. Even he would have been amazed at just how far physicists have pushed this experiment, and how it still continues to confound and challenge our intuitions about the nature of reality.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Abstract:

I will discuss our efforts to use machine learning (ML) to accelerate the computational tailoring and design of transition metal complexes for catalysis and metal-organic framework (MOF) materials in spaces of millions to tens of millions of materials. Traditionally, computational modeling with high-throughput screening based on density functional theory (DFT) has been employed for data generation either for direct discovery or when paired with regression ML models. I will describe how we have addressed some of the challenges of applying these workflows in regimes of scarce data. I will describe how we have achieved 1000-fold accelerated discovery of light-harvesting complexes, single-site catalysts, and energy storage materials. To accomplish this, we have quantified uncertainty using measures of the latent space to improve model confidence as well as to drive efficient global optimization workflows with multitask neural networks. I will also describe how we have leveraged natural language processing to extract, learn, and directly predict experimental measures of stability on heterogeneous MOF materials. I will also touch upon how we are beginning to overcome one chief limitation of accelerated catalyst discovery by using diffusion models to predict transition state structrues, the rate limiting step in conventional computational modeling of catalysts.

About the HGS MathComp Romberg Program:

With its founding in 2007 the HGS MathComp implemented the distinguished Romberg Guest Professorship. With this program the graduate school invites leading researchers working in a field relevant to the graduate school for a longer stay and to participate in the study training program.
The guests invited via the HGS MathComp Romberg Program make substantial contributions to the study program by complementing the teaching done by the members or by disseminating their latest research results at the school.

For more information please visit the website of the Romberg Program.

The lecture will be held in German and English.

The emergence and transmission of pathogens that cause infectious diseases is an increasing threat in Europe, fueled by climate change, globalization, increasing international mobility, amongst many other broad societal and environmental transformations. Since the 2000s, The Upper Rhine Valley in Southwestern Germany has emerged as a hotspot for invasive Asian tiger mosquitoes with their populations persisting despite control and eradication efforts by local and regional administrations.

To address the growing public health risk endemic Asian tiger mosquitoes populations pose in relation to the spread of infectious diseases, it is critical that efforts are undertaken to evaluate the conditions contributing to the establishment of Asian tiger mosquitoes populations as well as how efforts to mitigate and respond to climate change may actually make local environments more suitable to these disease vectors amongst others.

Join professors from Universität Heidelberg to learn about these threats and the impacts of climate change and mobility on disease vectors such as mosquitoes. Speakers will address current research at Universität Heidelberg and its partner institutions as well as the citizen science initiative Mosquito Alert which is working to tackle invasive mosquito populations across the globe.

Speakers:

Prof. Till Bärnighausen • Heidelberg Institute of Global Health (HIGH) & IWR
Dr. Norbert Becker • Centre for Organismal Studies (COS)
Prof. Joacim Rocklöv • IWR & HIGH
Prof. Carsten Wergin • Faculty of Behavioral and Cultural Studies
Prof. Alexander Zipf • Heidelberg Institute for Geoinformation Technology (HeiGIT) & GIScience

May 8, 2023 • 10:15 - 11:45
May 15, 2023 • 14:00 - 15:30

Machine learning holds great promise in accelerating chemical discovery and materials discovery. In the chemical sciences, data quality and availability are among the biggest challenges for predictive machine learning accelerated discovery. This includes whether electronic structure methods are sufficiently accurate for data generation or if experimental data of suitable quality is available. I will describe some techniques and approaches to overcome these limitations to design novel materials, including catalysts, photoactive complexes, and metal-organic frameworks

Datum: Do./Fr., 11./12.05.23. 09:00-15:00
Link Online-Registrierung [Workshop: „Fast am Ziel angekommen: Erfolgreich und gestärkt in die Disputation gehen]“

Beschreibung:

Eine lange Phase der wissenschaftlichen Ausbildung liegt nun hinter Ihnen. Nun liegt noch der letzte große Meilenstein, die mündliche Verteidigung, vor Ihnen. Wahrscheinlich schauen Sie diesem Tag nicht nur mit Gelassenheit und Freude entgegen, sondern es macht sich Zweifel und Nervosität breit.

Ausgehend von Ihren individuellen Erfahrungen werden Sie in diesem Workshop Präsentationstechniken und Verteidigungsstrategien kennenlernen, die es Ihnen ermöglichen, Ihre eigenen Forschungsergebnisse sicher und überzeugend darzustellen und auch für kritische Rückfragen gewappnet zu sein. Nur so können Sie souverän zwischen Leinwand und Publikum vermitteln.

Anhand von Ihrer zu Beginn durchgeführten kurzen Dissertations- Präsentation werden Sie ein differenziertes Videofeedback erhalten, um Ihre Stärken zu verdeutlichen sowie Möglichkeiten aufgezeigt, diese weiter auszubauen. Darüber hinaus werden der formale Ablauf und die spezielle Form der Prüfungssituation Teil des Workshops sein. Der Umgang mit Lampenfieber und Nervosität runden die inhaltliche Ausrichtung des Workshops ab, so dass Sie dem krönenden Abschluss Ihrer Dissertation gelassener entgegen sehen können.

Agenda (Themenauswahl):

- Kurz-Präsentation der eigenen Dissertation mit Videoaufnahme und professionellem Feedback

- Bausteine eines Diputationsvortrages

- Was muss ich bei der Vorbereitung meiner Disputation besonders beachten? (Do’s and Don’ts)

- Wie kann ich überzeugend und souverän meine Forschungsleistung vorstellen?

- Wie gehe ich mit Lampenfieber und Nervosität um?

- Welche Reaktions- und Verteidigungsstrategien gibt es und wie kann ich diese einsetzen?

- Wie ist der formale Ablauf in dieser speziellen Prüfungssituation?

Zur Trainerin:

Dr. Angelika Wolf, MethoDactics

Frau Dr. Wolf hat durch mehrjährige und vielfältige Tätigkeiten zahlreiche Erfahrungswerte im Bereich der Erwachsenenbildung, Hochschulforschung, des Wissenschaftsmanagement und in der Wirtschaft gesammelt, die die Inhalte ihrer Workshops prägen. Ihre Promotion hat sie an der Pädagogischen Hochschule Heidelberg an der Schnittstelle von Psychologie und Physikdidaktik abgelegt. Seit 2017 arbeitet sie als freie Trainerin & Karriereberaterin in Deutschland und in der Schweiz (MethoDactics).

Arbeitsschwerpunkte: Persönlichkeitsentwicklung - Gestaltung individueller Karriere- und Lebenswege - Netzwerken in der Wissenschaft; Professionelle Weiterbildung - Wissenschaftliches Arbeiten- quantitative Forschungsmethoden - Disputationstraining

Organized by the Scientific Software Center (SSC).

Summary:
The course will give a brief overview of best practices for the sustainable development of research software. Areas covered are e.g. version control, development workflows, licensing, documentation, software testing, CI/CD, packaging, static code analysis, clean code. The course will emphasize the importance of these topics for the development process, give opinionated tooling recommendations and share experiences. The primary goal of the course is to enable the participants to formulate a roadmap of courses and self-learning activities to further improve their software development skills.

Registration required!

For more information please visit the website of the SSC:
https://ssc.iwr.uni-heidelberg.de/events

May 2-4, 2023

SIMPLAIX is a cooperation between the Heidelberg Institute for Theoretical Studies (HITS), the Karlsruhe Institute of Technology (KIT) and Heidelberg University, focussed on bridging scales from molecules to molecular materials by multiscale simulation and machine learning (www.simplaix.org). The aim of the workshop is to bring together scientists working in the field to share their research and discuss current challenges.

Registration is now open. Registration deadline: 15 March, 2023.

For further information please visit the website of the workshop: https://simplaix-workshop2023.h-its.org/

Organizers:
Rebecca Wade (HITS) • Andreas Dreuw (IWR, Heidelberg University) • Frauke Gräter (HITS) • Fred Hampreccht (IWR, Heidelberg University) • Ganna Gryn'ova (HITS) • Marcus Elstner (KIT) • Pascal Friedrich (KIT) • Ullrich Köthe (IWR, Heidelberg University)

Machine learning galore will feature lab presentations by PIs as well as scientific talks by junior scientists.

Lab presentations:
• Ralf Klessen
• Johannes Schemmel
• Michael Strube

Science talks:
• Victor Ksoll (Klessen lab): 3D reconstruction of interstellar dust distributions with invertible neural networks
• Luca Blessing (Schemmel lab): Event-based Backpropagation for Analog Neuromorphic Hardware
• Wei Zhao (Strube lab): Graph Neural Networks on the Manifold of Symmetric Positive Definite Matrices

To help plan the catering, please register for free by clicking here.

Scientific Machine Learning is a joint initiative from STRUCTURES and IWR aimed at fostering interactions within and development of the local machine learning community. Its portal, http://mlai.uni-heidelberg.de summarizes the many relevant events and news from across campus that would otherwise remain scattered across single institutions or fields.

The goals of the MLAI platform align with the STRUCTURES Cluster of Excellence's objective of driving research into the fundamental understanding of current and future machine learning, and with IWR’s aim to leverage machine learning to enable the solution of long-standing problems in the natural and life sciences, the engineering sciences, as well as the humanities.

Further information and links:

MLAI homepage
Machine Learning Talks on Campus – Information service and mailing list
STRUCTURES Cluster of Excellence

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Abstract:

The Portal of Medical Data Models (medical-data-models.org) is a multilingual information infrastructure for medical research based on FAIR principles. It provides Europe’s largest collection of medical forms with semantic annotation. Medical metadata can be reused efficiently to build medical databases compliant with standards from regulatory authorities (model-driven software development). Contents can be exported in 20+ formats and used directly in an integrated open source EDC system, which provides an interface to electronic health record (EHR) systems used in routine patient care.

The talk will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.

Zoom Link:
https://eu02web.zoom.us/j/62842665374?pwd=M21aaStjZWRndUdrTzBaM2hRRnJjdz09

Abstract:
The world is changing rapidly, accelerating our need to understand how factors like climate, land use, and social structure affect the ecology of disease on a global stage. Interrogating these processes requires applying advanced analyses across broad datasets to ensure that results are generalisable and complexities are well-understood. However, often, disease ecology analyses take relatively coarse species-level approaches that are fraught with sampling biases and are restricted in their ability to inform finer-scale processes. Further, when these models are used to predict the disease consequences of global change they can be difficult to validate, reducing our confidence in their predictions.

In this talk, I present a series of analyses that we have used to identify macroecological trends of host-pathogen ecology and the changing structure of the global host-virus network, and our efforts to use them to predict elements of global change. I compare and contrast them with other finer-scale studies of disease dynamics that comprise most of the field of disease ecology, and I outline the ways we are attempting to move between these scales of investigation. Ultimately, I discuss the need for “bottom-up” mechanistic prediction of disease dynamics in novel systems, using fine-scale analyses to inform the most important global-scale problems.

“Mathematics of Life” is a special interest group organized by doctoral students of the HGS MathComp.

Link Mathematics of Life:
www.mathcomp.uni-heidelberg.de/mathematics-of-life

March 27-30, 2023 • 10:00-12:00 & 13:00-15:00

This 4-day course offers a compact introduction to mathematical optimization. We invite researchers in non-mathematical fields as well as in mathematics to attend the classes.
The goal of the course is to enable the participants to recognize the characteristics of a given optimization problem, to understand its difficulties and limitations, and to choose suitable solution methods as well as to develop ideas on how to model problems from their own field as optimization problems.

We will focus on the following four categories of optimization problems:
day 1) unconstrained optimization
day 2) convex optimization
day 3) nonlinear optimization
day 4) infinite-dimensional optimization

For each of these problem classes, we will study meaningful examples, the relevant theory, and prominent solution algorithms. Every day consists of a 90-minute lecture part in the morning and a 90-minute hands-on exercise session in the afternoon.

REGISTRATION REQUIRED !
Please register via the office of the graduate school: hgs@iwr.uni-heidelberg.de

For further information please visit the website:
https://scoop.iwr.uni-heidelberg.de/teaching/2022ws/short-course-optimization/

Target audience: BSc students in Mathematics and Computer Science

This event is a double seminar between MATHEMATIKON, Heidelberg and AIMS, South Africa on the occasion of the International Day of Mathematics. In two short and interactive lectures we celebrate the day of mathematics and bring together students from the two institutions on a virtual platform.

The event is organized by "heiAIMS, the Heidelberg - Cape Town Network for Applied Mathematics and Scientific Computing" which is funded by the Baden-Württemberg-STIPENDIUM for University Students, a program established by the Baden-Württemberg Stiftung.

###

Title: Mathematics and African Arts
Speaker: Dr. Mafoya Landry Dassoundo • Department of Mathematical Sciences, African Institute for Mathematical Sciences (AIMS)

Abstract:
First of all, we will define, and recall basic the properties of braids groups and connect them naturally with knot theory. Some of its applications in the hairstyles of African women will be presented. Secondly, we will share a cultural experience around one of the oldest African games well known as "African stones game".

###

Title: What Exactly is Infinity?
Speaker: Dr. Michael Winckler • HGS MathComp

Abstract:
The concept of infinity is hard to understand for humans. Counting finite sets is a natural concept, but understand what countably infinite sets are and that we can even investigate uncountably infinite sets is difficult to comprehend.

In this lecture we will start by comparing finite sets and establishing a rigorous method to compare sets in their size. Expanding this to infinite sets will help us to move forward and show that different levels of infinity exist. We will conclude the lecture by trying to visualize our results in drawing space-filling curves, thus experiencing that our notion of size does not easily extend to infinity.

Remark: Please bring paper and a pencil to class

This will be a short presentation about the (Julius) Springer publishing house and contemporary academic publishing. We will begin by briefly touching upon Springer’s historical connections to the University of Heidelberg before providing some insights into the modern publishing process. In particular, we will offer hints as to how to successfully publish journal articles and books of various types, and take questions from the audience. This should be especially useful for graduate students and early-career researchers.

Following the lecture, there will be a get-together. It will take place in the adjoining Common Room at 17:00. Snacks and beverages will be provided.

This event is jointly organized by HGS MathComp and the Faculty of Mathematics and Computer Science.

In this talk we discuss randomization techniques for solving large scale linear algebra problems. We focus in particular on solving linear systems of equations and eigenvalue problems. We first introduce a randomized Gram-Schmidt process for orthogonalizing a set of vectors and its block version. We discuss its efficiency and its numerical stability while also using mixed precision. Further randomized GMRES and randomized FOM methods are discussed for solving linear systems of equations as well as randomized Rayleigh-Ritz procedure for solving eigenvalue problems.

The IWR Colloquium will be streamed via Zoom. For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Having access to a powerful generative model allows for a wide range of downstream applications, such as probabilistic inference, sampling, data completion, density evaluation, outlier detection, etc. Diffusion models (DMs) are an emerging class of deep generative models that have demonstrated remarkable synthesis quality. DMs rely on a diffusion process that gradually perturbs the data towards white noise, while the generative model learns to denoise. A major drawback of DMs, compared to, for example, Generative Adversarial Networks, is that sampling can be relatively slow.

In this seminar, I will give an accessible introduction to DMs and present our work on critically-damped Langevin DMs (CLD) which is based on ideas from statistical mechanics. CLD can be interpreted as running a joint diffusion in an extended space, where the auxiliary variables can be considered "velocities" that are coupled to the data variables as in Hamiltonian dynamics. CLD significantly accelerates sampling compared to the original DM formulation, however, many further improvements can be made by borrowing ideas from the ODE solver literature.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Our brains are comprised of billions of neurons that form a complex network. This network is a result of both evolutionary optimization (fostering a modular arrangement including highly specialized areas) and our own experience (storing memories and skills by adapting connection strengths) and determines how we process sensory input to produce meaningful responses. Since neurons communicate with short electrical pulses only when necessary, they are extremely energy efficient. Given our worldwide increase in computing demand, there is thus a strong incentive to develop low-energy neuromorphic computing paradigms that mimic the working principles of the brain. But what are the relevant working principles of the brain? How does a neural network develop useful dynamics? In this seminar, I will present minimal principles to ensure stable collective neural dynamics from a statistical physics perspective, discuss how these can be used to tune network states to task requirements and show how they can be applied to neuromorphic computing. While I mainly focus on experience-driven self-organization, I will finish with some ideas to include evolutionary-driven architectures in the future.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

“Mathematics of Life” is a special interest group organized by doctoral students of the HGS MathComp.

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

The MBO scheme is an efficient algorithm for data clustering, the task of partitioning a given dataset into several meaningful clusters. In this talk, I will present the first rigorous analysis of this scheme in the large-data limit.
The starting point for the first part of the talk is that each iteration of the MBO scheme corresponds to one step of implicit gradient descent for the thresholding energy on the similarity graph of the dataset. It is then natural to think that outcomes of the MBO scheme are (local) minimizers of this energy. We prove that the algorithm is consistent, in the sense that these (local) minimizers converge to (local) minimizers of a suitably weighted optimal partition problem.
To study the dynamics of the scheme, we use the theory of viscosity solutions. The main ingredients are (i) a new abstract convergence result based on quantitative estimates for heat operators and (ii) the derivation of these estimates in the setting of random geometric graphs.
To implement the scheme in practice, two important parameters are the number of eigenvalues for computing the heat operator and the step size of the scheme. Our results give a theoretical justification for the choice of these parameters in relation to sample size and interaction width.
This is joint work with Jona Lelmi (University of Bonn).

The lecture will be also streamed online: https://us02web.zoom.us/j/4889309058

Minicourse: Introduction to Mathematics of Deep Learning
Leonid Berlyand • Pennsylvania State Universtiy, USA
October 26-27, 2022 • 14:30 - 16:30

Abstract:
The goal of this minicourse of four lectures is to introduce basic concepts from deep learning in a rigorous mathematical fashion, e.g introduce mathematical definitions of deep neural networks (DNNs), loss functions, the backpropagation algorithm, etc. We attempt to identify for each concept the simplest setting that minimizes technicalities but still contains the key mathematics. This minicourse follows the upcoming book “Mathematics of Deep Learning: an introduction” by L. Berlyand and P.-E. Jabin. Publisher: De Gruyter (to appear).

Lecture 1. History, general perspective and basic notions of deep learning

In this lecture, we briefly discuss the general perspective of machine learning:
what is it and why study it? Next, we introduce the classification problem in a supervised learning context and then introduce the key concept of artificial neural networks (ANNs) as the composition of linear maps and nonlinear activation function followed by other basic definitions describing ANNs.

Lecture 2. DNNs and approximation theory

In this lecture, we discuss the universal approximation theorem describing the wide class of continuous functions which DNNs can be used to approximate. This theorem explains the extensive use of DNNs in classification problems. Next, we introduce the concept of training via the gradient descent algorithm which improves the approximate classifier by iteratively __learning__ from the dataset.

Lecture 3. Backpropagation & CNNs

We begin from introducing the notion of computational complexity. Next, we introduce the backpropagation algorithm which significantly reduces the computational cost of optimizing the loss function. This is done in the simplest one neuron per layer setting, which while not practical allows us to explain the concept without many technicalities. Finally, if time permits, we briefly discuss convolutional neural networks and their properties.

Lecture 4. Implementing DNNs and Training: a brief overview of Pytorch

This lecture will be presented by my co-author P.-E. Jabin (Penn State).

We present here a short and very basic introduction to Pytorch, in the context of classification of images. We assume passing familiarity with coding and with python in particular. Many further tutorials exist online and several can be found at https://pytorch.org/tutorials/
For more see the abstract_file:

From the vision “Stability, Prosperity and Sustainability,” Thailand has adopted “Thailand 4.0” as a policy vision for economic development which aims at driving the country out of a middle-income towards a high-income economy. Underlying this is no other than an attempt to change from the current economic model towards an “innovation-driven economy”—i.e., transitioning from an industry-driven development to a technology-, creativity-, and innovation-driven development by consolidating as well as integrating various fields of knowledge. This, thus, necessitates deepening mathematical research on optimization and numerical methods as it plays a considerable role in providing solutions for a variety of problems including those in such areas as industry, finance, engineering, economics and agriculture.

Realizing the importance of research on optimization and numerical methods, the Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi—in cooperation with the Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, the Federal Republic of Germany, and along with the nationwide as well as the Southeast Asian regionwide network of universities including Walailak University, Prince of Songkla University (Pattani Campus), Chulalongkorn University, Silpakorn University, Mahidol University, Chiang Mai University, and King Mongkut’s University of Technology North Bangkok—will organize an international “Workshop on Computational Science 2022: Webinar on Optimization and Numerical Methods in Industries.”

This year, the Department will co-host the event with the Department of Mathematics, School of Science, Walailak University, and the Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University.

Scientific progress in machine learning is driven by empirical studies that evaluate the relative quality of models. The goal of such an evaluation is to compare machine learning methods themselves, not to reproduce single test-set evaluations of particular optimized instances of trained models. The practice of reporting performance scores of single best models is particularly inadequate for deep learning because of a strong dependence of their performance on various sources of randomness. Such an evaluation practice raises methodological questions of whether a model predicts what it purports to predict (validity), whether a models performance is consistent across replications of the training process (reliability), and whether a performance difference between two models is due to chance (significance). The goal of this tutorial is to provide answers to these questions by concrete statistical tests.

The tutorial is hands-on and accompanied by a textbook (Riezler & Hagmann: Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers, 2022) and a webpage including R and Python code: https://www.cl.uni-heidelberg.de/statnlpgroup/empirical_methods/

! REGISTRATION REQUIRED !
Please register via the office of the graduate school: hgs@iwr.uni-heidelberg.de

In this talk I will present a geometric multilevel optimization approach choosing as case study a regularised inverse problem. In particular, the approach is motivated by variational models that arise as the discretization of some underlying infinite dimensional problem. Such problems naturally lead to a hierarchy of discretized models. We employ multilevel optimization to take advantage of this hierarchy: while working at the fine level we compute the search direction based on a coarse model. By utilising concepts of information geometry in our formulation, we propose a smoothing operator that only uses first-order information and incorporates constraints smoothly. We show that the proposed algorithm is well suited for ill-posed reconstruction problems and demonstrate its efficiency on several large-scale examples.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

In statistics, stochastic processes are the main tool for modelling spatial and temporal data, and the most commonly used type are the Gaussian processes. A popular approach to define Gaussian processes is through linear stochastic differential equations driven by white noise. This methodology is often denoted the SPDE approach. By utilising methods from numerical analysis one has been able solve several of the computational bottlenecks that have hampered the usage of Gaussian processes for real world data sets, in particular for spatial statistics. I will focus on how one can apply the same methodology to create non-Gaussian processes, in space and time. I will also discuss what practical properties these processes have over their Gaussian counterpart. Further, I will present very recent work where we have extended the SPDE approach for Gaussian process, to Euclidean graphs (like street networks). Here the linear differential operators are obtained using Quantum graphs, which opens these methods for a new wide range of applications.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

The graduate school HGS MathComp will organize an Integrative Think Tank (ITT) from July 4-8, 2022 in Heidelberg.

What is an "Integrative Think Tank" (ITT)?
ITT is a 1-week-challenge workshop with two industrial partners. Students and lecturers work together with experts from the companies to investigate R&D topics related to current developments at these companies.

What is the goal of the event?
The goal of the event is to formulate actual research topics as thesis projects outlines (master or PhD). After the event the University and the partner companies join forces to convert the project outlines into actual research projects.

Who can participate?
The event is open to all master and PhD students at Heidelberg University. ITT is most successful if different students from various fields work together to analyze the research questions of our partners.

What is the reward?

• All participants get a certificate of attendence that certifies 2 ECTS as key competence training.
• Attending students can also apply to participate in the projects defined at ITT as their master or PhD project.
• On top you get direct contacts to the participating companies for internships and practicals (or later employment ...).

OK, you got me! How do I register?
Scroll to the end of the page and find all details regarding registration. Get some more information along the way! And: Tell your friends about it! The more, the merrier!

For more information please visit the website:

www.mathcomp.uni-heidelberg.de/itt-2022

Predicting the emergent properties of a material from a microscopic description is a scientific challenge. Machine learning and reverse-engineering have opened new paradigms in the understanding and design of materials. However, the soft-matter field has lagged far behind in embracing this approach for materials design. The main difficulty stems from the importance of entropy, the ubiquity of multi-scale and many-body interactions, and the prevalence of non-equilibrium and active matter systems. The abundance of exotic soft-matter phases with (partial) orientation and positional order like liquid crystals, quasicrystals, plastic crystals, along with the omnipresent thermal noise, makes the classification of these states of matter using ML tools highly non-trivial. In this talk, I will address questions like: Can we use machine learning to autonomously identify local structures, detect phase transitions, classify phases and find the corresponding order parameters in soft-matter systems, can we identify the kinetic pathways for phase transformations, and can we use machine learning to coarse-grain our models? Finally, I will show how one can use machine learning to reverse-engineer the particle interactions to stabilize nature’s impossible phase of matter, namely quasicrystals?

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Deep learning-based approaches have revolutionized virtually all domains of computer vision, including the field of microscopy image analysis. In image reconstruction and classification, in segmentation and artificial labelling, they have pushed both flagship projects and bread-and-butter everyday tasks, allowing image analysis to keep pace with the recent advancements in imaging technology and instrumentation. I will talk about the recent work of my group that has enabled the first segmentation of cells in a whole animal imaged with electron microscopy, our collaboration with microscope developers for trusted reconstruction of light field microscopy and our current efforts to reduce the annotation budget for training of segmentation algorithms. I will also show how we strive to make our methods accessible to biologists without computational expertise through our software ilastik and through the emerging community network collection at the BioImage Model Zoo.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Datum:
10.05.2022 und 12.05.2022 (14:00-16:30 Uhr)

Beschreibung:
Vielfalt und Pluralität sind mittlerweile Alltag in unserer Gesellschaft, im Privat- und Berufsleben: Menschen mit unterschiedlichsten Lebensentwürfen, Hintergründen, Glauben oder Herkunft treffen aufeinander.

In dem zweiteiligen Workshop werden wir uns mit verschiedenen theoretischen Ansätzen im Themenfeld Diskriminierung beschäftigen und anhand praktischer Übungen einen eigenen erfahrungsbasierten Zugang dazu finden. Ziel ist es, Selbstverständlichkeiten und gängige Narrative diskriminierungskritisch zu hinterfragen sowie Handlungsoptionen aufzuzeigen, die tradierte Verhaltensmuster aufbrechen können. Ein besonderes Augenmerk soll dabei auf die Geschlechtergleichberechtigung gelegt werden.

Dozentinnen:
Halszka ?liwa-Ohnesorge verantwortet die Bildungsstelle Plurales Heidelberg bei Mosaik Deutschland e.V. Sie studierte Religionswissenschaft und Politikwissenschaft Südasiens an der Universität Heidelberg. Nachdem Studium arbeitete sie u.a. für ein ziviles, indisch-pakistanisches Friedensprojekt, bei dem die gleichberechtigte Förderung von Jungen und Mädchen ein zentrales Element war. Heute liegt der Schwerpunkt ihrer Arbeit auf der vorurteilsbewussten und diskriminierungskritischen politischen Bildung.

Lara Track leitet das Antidiskriminierungsbüro Heidelberg (ADB) bei Mosaik Deutschland e. V. Sie berät Menschen, die Diskriminierung erfahren haben und setzt sich in Netzwerken auf kommunaler, Landes- und Bundesebene gegen Diskriminierung ein. Im Rahmen ihrer wissenschaftlichen Mitarbeit am Historischen Seminar der Universität Heidelberg erforscht sie Verbindungen zwischen Frauenfriedensaktivismus und Feminismus in den USA. In der Auseinandersetzung mit US-Feminismen gründet ihr Interesse am Konzept der Intersektionalität, das in der mehrdimensionalen Beratung im ADB zum Tragen kommt.

Zielpublikum:
Mitarbeiterinnen und Mitarbeiter in der Verwaltung, PostDocs, Junior Forschungsruppenleiterinnen und -leiter

! ANMELDUNG ERFORDERLICH !
Anmeldungen für den Workshop bitte an: hgs@iwr.uni-heidelberg.de
[Anmeldeschluss: 18.04.2022]

Netzwerken ist ein wesentlicher Bestandteil bei der Entwicklung einer wissenschaftlichen Karriere. Die Analyse, der Aufbau und die Pflege von (wissenschaftlichen) Netzwerken unterstützen auf dem Weg zur Professur aber auch bei außeruniversitären Karrierezielen. Dabei gilt es die eigene komplexe Forschungstätigkeit in sich bietenden Situationen innerhalb (z.B. wissenschaftliche Gemeinschaft, Konferenz) und außerhalb (z.B.: Fördereinrichtungen, Wirtschaft) der Wissenschaft überzeugend und verständlich darzustellen.

In diesem Workshop geht es darum, sich auf Netzwerksituationen wie bspw. den Besuch einer wissenschaftlichen Konferenz vor- und nachzubereiten. Dazu werden verschiedene Situationen vorgestellt und in Übungen und Rollenspielen mit Videoaufzeichnungen (falls gewünscht) ausprobiert und im Detail besprochen.

Des Weiteren wird das eigene Netzwerk analysiert, um Potentiale für dessen Weiterentwicklung zu erkennen und diese bei entsprechenden Netzwerkgelegenheiten zu nutzen. Überdies werden die besten Tricks und Kniffe für erfolgreiches Smalltalken vermittelt, um die eigene Kommunikation in Alltag und Beruf zu optimieren.

Themenauswahl:
• Netzwerkpotenziale: Was ist Netzwerken und warum brauche ich es?
• Netzwerkanalyse im Kontext Wissenschaft – die Rolle von Mentoren
• Analyse, Aufbau und Pflege von (wissenschaftlichen) Netzwerken – wie sieht mein eigenes Netzwerk aus?
• Methodentools: Elevator Pitch zur (überzeugenden und verständlichen) Darstellung von komplexen Forschungstätigkeiten
• Methodentool: „Conference Dinner/Conference Break“
• Methodentool: „Erfolgreiche Selbst-Präsentation“: Story Telling und Grundregeln für erfolgreiches Smalltalken

Zielpublikum:
Dieser Workshop ist Teil des Upstream Programms und nur für weibliche Mitglieder zugänglich.

! ANMELDUNG ERFORDERLICH !
Anmeldungen für den Workshop bitte an: upstream@iwr.uni-heidelberg.de

Der Datenbank- und Softwareriese SAS öffnet seine Türen für Mathematikerinnen und Frauen* aus den STEM-Feldern! Euch erwarten Vorträge und Hands-On-Erfahrungen mit den SAS-Toolsets sowie die Möglichkeit zur Vernetzung mit dem Women´s Initiative Network von SAS.

Zielpublikum:
Diese Exkursion ist Teil des Upstream Programms und nur für weibliche Mitglieder zugänglich.

! ANMELDUNG ERFORDERLICH !
Anmeldungen für den Workshop bitte an: upstream@iwr.uni-heidelberg.de

Topic:
Natural or engineered materials often contain two or more key constituents, arranged in a heterogeneous structure varying at different scales. Such materials are desirable because their macroscopic properties can be superior to the properties of the individual constituents. It is even possible to explicitly design them for a particular purpose by changing the composition of the constituents.

An example are carbon fibre composites for lightweight structures and vehicles. The mathematical modelling of such heterogeneous or composite materials typically leads to PDEs with highly oscillating coefficients. Direct numerical solution of such problems with traditional methods, such as finite elements is computationally expensive. Just to compute the correct qualitative behaviour, the mesh resolution would need to be sufficiently high to capture all the fine scale variation.

In this seminar, we will study multiscale numerical methods that address various aspects of this challenge. This includes the generation of low-dimensional yet high-quality approximation spaces, acceleration of fine-scale solutions and efficient uncertainty quantification for multiscale problems.

Each student will present a key publication on multiscale numerical methods with an aim to cover most aspects of the field.

Prerequisites:
Basic knowledge of partial differential equations, Sobolev spaces and Finite Element methods is required. For the uncertainty quantification topics, basics of probability theory are needed.

Registration and Schedule:
• First meeting: April 22, 2022, 13:00. Room: TBA
• Since we use MÜSLI for email communication, please register at: https://muesli.mathi.uni-heidelberg.de/lecture/view/1517
• Schedule: Will be chosen on first meeting to maximize attendance

Contact:
Main contact - Linus Seelinger: linus.seelinger at iwr.uni-heidelberg.de
Secondary contact - Robert Scheichl: r.scheichl at uni-heidelberg.de

Talks:
The length of each talk is 40 min. + 10 min. for questions and discussion.
Before your talk you should meet with one of us to discuss your presentation.

Have you sat in front of an empty sheet of paper or an empty file before, trying to start a report, a paper or your PhD Thesis, but struggling to make progress? Or have you had to read a research article relevant to your PhD project that was so incomprehensible or dry that you were wishing to be somewhere else for the day to end? Good scientific writing is an absolutely essential part of our work as researchers; only through good communication will we be able to captivate the audience and truly enthuse them for our achievements and results. It is as important as pure academic ability for a successful professional career in academia, but also in industry, but typically we are not trained formally in good writing in a mathematics or science degree. In this crash course I aim to give you some useful pointers on good writing in the mathematical sciences, and through some hands-on exercises we will try to immediately put them in practice.

! REGISTRATION REQUIRED !
Please register via the office of the graduate school: hgs@iwr.uni-heidelberg.de

Prof. Morteza Fotouhi • Sharif University of Technology

Dates:
April 20, 2022 / 09:00-12:00
April 21, 2022 / 14:00-17:00

The term moving interfaces and free boundary refers to a class of problems in which the domain of the problem itself is also an a priori unknown, as well as the basic unknown solution to governing equations. Hence, finding the domain is part of the problem.
In this lecture I shall present some basic models in moving interfaces and free boundary problems. These includes obstacle problem, Stefan problem, Hele-Shaw flow and Muskat problem.
I will also review the state of art for obstacle problem. The lectures will be at elementary level for both advanced master and Ph.D. students.

! REGISTRATION REQUIRED !
Please register via the office of the graduate school: hgs@iwr.uni-heidelberg.de

! REGISTRATION REQUIRED ! Please register via hgs@iwr.uni-heidelberg.de (Deadline: March 22, 2022)

The workshop will held as an in-person event. All regulations regarding the current Coronavirus Ordinance of Heidelberg University apply. If the situation changes the workshop will be held as a virtual event.

March 29-30, 2022 • 09:00
May 2, 2022 • 14:00-18:00

---------------------------------------------------------------------------

Working as a PhD student you have the challenging task of developing research findings and write you doctoral thesis within three years. This alone is a demanding job. In addition, it is vital to the scientific process that your findings are presented to the scientific community. For most PhD students this is the first big project in their professional life and it could have a crucial impact on their future professional career. PhD students are highly motivated when they start their PhD studies but may underestimate the need for professional management for this three-year project "doctoral thesis".

This seminar demonstrates how to approach the doctoral thesis in a professional way. Project management tools and techniques are used, tailored to the specific situation of PhD students. You will learn how to set a project vision, define clear objectives, gain buy-in from your supervisor and other colleagues in your group, and how to develop a project plan, which is structured and at the same time flexible enough to easily adjust to unexpected findings. You will establish a "controlling cycle" which helps you to recognise risks and problems as early as possible, and you will learn how to manage critical situations and deal with ups and downs. Furthermore, networking with colleagues, supervisors and other people are important topics of this seminar.

Throughout the seminar, you will work on your own doctoral thesis and share your experience with others. This seminar is most beneficial for PhD students who are in the early phases of their doctoral thesis. At the end of the seminar you will have established a strategy on how to approach your own doctoral thesis. During the follow-up REVIEW we will share experience and best practices and deal with open questions from the first module.

This seminar will help you to make the most effective use of your three years and finish your doctoral thesis on time.
You will also learn and practise the basic concepts of project management – a prerequisite in industries and research institutions.

Uncertainty quantification plays an important role in many engineering applications. In this talk we discuss some recent advancements in the approximation of high-dimensional functions appearing in this context. We provide new results for surrogate modeling and parameter estimation in cases where the uncertainty is described by a Gaussian random field. Additionally we address how the usage of neural networks to learn linear and nonlinear operators may help in solving such tasks, and what possible challenges might lie ahead.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
If your are planing to attend in person you have to follow the 3G-rule set (vaccinated / recovered / tested).
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

We all have different networks - no matter whether we call them "network" or not. These networks provide support, advice and help in different fields. To better use and understand them it is crucial to be aware of the fact that the purpose influences the network itself. If our purpose (or aim or goal) remains unclear efficient networking is impossible. The workshop "Purposeful Networking" provides basic information on networking and gives space to clarify personal aims - to create a link between network and purpose.

Registration: hgs@iwr.uni-heidelberg.de
Registration Deadline: January 24, 2022

Please note that participation in person (max. 25) will be on first come first served basis prior registration via e-mail to:
wissrech@iwr.uni-heidelberg.de

In addition the Colloquium will be streamed via Zoom.

For more information please visit the website:
www.iwr.uni-heidelberg.de/events/iwr-colloquium

---------------------------------------------------------------------------

Spatial and temporal control of molecular phenomena is crucial to develop intelligent materials for applications ranging from sensing over catalysis to photonic computing. In this regard, stimuli-responsive molecules enable to influence structural and dynamic properties at the atomic level in a highly controlled manner by external stimuli such as light.

To transfer external inputs into functionality, a detailed understanding of both, the operation mechanism of the responsive species and their impact on the environment, is needed. In the presentation, I will give an overview of our activities on developing and applying theoretical methods to investigate the dynamics of stimuli-responsive systems at different time and length scales. By establishing an automated and first-principle based parametrization approach for interatomic potentials, investigations of equilibrium and out-of-equilibrium phenomena in responsive and functional materials are performed.

My presentation is divided in three parts, which cover our atomistic investigations on (i) responsive molecular species (e.g. molecular switches/machines), (ii) the dynamic intermolecular interplay during molecular aggregation and atomically precise restructuring and (iii) hierarchal and responsive architectures (e.g. phase change material and functionalized Metal-Organic Frameworks). By directly linking of our multi-scale simulations with experimental techniques, our work contributions to a rational development of responsive and functional materials.

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

The short course is organized by:
Prof. Eva Gutheil • IWR, Heidelberg University
Dr. Nora Urbanetz • Daiichi Sankyo Europe GmbH, Pfaffenhofen/Ilm

Participation is possible after registration:
Please send full name, affiliation, position and Email address to
Ellen Vogel: ellen.vogel@iwr.uni-heidelberg.de
For more see the abstract_file:

Large-scale optimization is a vibrant field with many ties to neighboring areas including analysis, numerical linear algebra, differential geometry, machine learning and partial differential equations. This presentation showcases these connections using past and ongoing projects in our recently established group "Scientific Computing and Optimization". I will also address open problems and future directions in the field and advertise opportunities for collaboration.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
If your are planing to attend in person you have to follow the 2G-rule set (vaccinated / recovered).
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Many engineering applications require the numerical evaluation of time-harmonic wave propagation problems over a range of frequencies. The most used technique to discretize partial differential equations is the finite element method. Due to the oscillations of analytical solutions the finite element discretization often becomes computationally expensive.

Model order reduction methods provide reliable approximations of the solution at low computational cost. In particular, they allow very fast responses both for real-time and multi-query contexts.

This talk deals with novel model order reduction techniques tailored to time-harmonic wave problems relying only on a precomputed set of snapshots, they present great flexibility, since they allow the construction of a surrogate starting from snapshots obtained via black-box solvers (e.g., commercial software).

The method’s efficiency is investigated in several examples, including transmission-reflection and scattering problems. Especially in the context of optimal control problems, where standard numerical techniques are unfeasible, the employment of surrogate models is crucial.

IMPORTANT: in person meeting changed to ONLINE ONLY meeting
Unfortunately this meeting will only take place online due to the COVID-19 situation.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

It’s not only the research topic itself. Many doctoral candidates also struggle managing all the different tasks relates to research, teaching and career development. Techniques and tools for time management provide help to develop a better structure for time management. One of these tools is a Gantt diagram that allows to plan long-term projects. Other tools will be introduced in the workshop. And there will be space to exchange on experiences and ideas.

Registration: hgs@iwr.uni-heidelberg.de
Registration Deadline: October 29, 2021

Deep learning is fueling advances and breakthroughs in a dizzying array of data-intensive scientific fields. In this talk, I will highlight recent and ongoing work of our lab that leverages deep learning to push the limits of advanced microscopy.
A long-standing challenge in the life sciences is to visualize biological cells at high resolution and with high throughput. Single molecule localization microscopy (SMLM) is among the most powerful and widely used super-resolution imaging methods, but is typically very slow and low throughput. I will present ANNA-PALM, a computational technique based on deep learning that can reconstruct high resolution views from strongly under-sampled SMLM data and widefield images, enabling considerable speed-ups without any compromise on spatial resolution. I will also highlight Shareloc, an online platform to facilitate the sharing and reanalysis of SMLM data, and Imjoy, a computational platform dedicated to facilitating the uptake of state-of-the art deep learning methods in the biomedical research community.

The IWR Colloquium will be held as an in-person event at the Mathematikon. In addition it will be streamed via Zoom.
If your are planing to attend in person you have to follow the 3G-rule set (vaccinated, recovered, tested).
For more information please visit the website of the colloquium.

Link: www.iwr.uni-heidelberg.de/events/iwr-colloquium

HGS MathComp Members will receive 1 ECTS credit for every 4 talks attended. Please make sure to include them in your BlueSheet.

Aim:

Bring together researchers from geography, chemistry, biology, hydrology, social sciences, applied mathematics and scientific computing to foster interdisciplinary exchange on the various aspects of water availability and quality.

Format:

Depending on the pandemic situation in the fall, the workshop will either take place as in person event or an online event. Depending on the demand a hybrid format is possible as well, so that participation is also possible without travelling.

Topics:

- Socio-hydrology and water resources management
- Environmental contamination and remediation
- Sustainable technology for water purity
- Cryosphere dynamics

! REGISTRATION REQUIRED !

For more information please visit the webpage of the workshop.

The school will be a hybrid event with live sessions at both places and streaming to offsite participants and is jointly organized with the
Indo-German Partnerships in Higher Education (IGP) Programme.

Aim:

Bring together PhD candidates from Mathematics, Computer Science and Scientific Computing to study the interplay of efficient numerical algorithms with modern computer hardware.

Format:

First week (October 4-8) is filled with lectures covering all aspects from hardware, programming models and algorithms to applications.

Second week (October 11-15) features small projects lead by a pair of supervisors from India and Germany.

Topics:

- Aspects of modern processor architectures
- Programming models and accelerator programming
- Scalable methods for solving partial differential equations (PDEs)
- Optimal control of PDEs
- Large-scale Bayesian inference and data assimilation
- Energy-aware numerical methods

! Application Deadline: August 20, 2021 !

For more information please visit the website of the school.

Dieser Workshop richtet sich an Wissenschaftler*innen, die vor der Aufgabe stehen, ihre berufliche Laufbahn (- innerhalb oder außerhalb der Wissenschaft -) zu planen.
Durch Einzel- und Kleingruppenarbeit, Impulse der Trainerin und Peer-Coaching wird Ihnen die Möglichkeit geboten, Ihre persönliche Situation zu reflektieren, berufliche und persönliche Ziele zu entwickeln und erste Schritte zur Umsetzung zu planen.

Modern application problems in the sciences rely heavily on data processing and modeling of systems and dynamics. The development of new and improved methods in mathematics and computer science aim to provide the tools and the theoretical background for these methods.

This 4EU+ summer school gives insights into several areas were current research heavily influences method development. Participants will get short, precise and high-powered introductions into several research fields. The aim is to provide the first step for young researchers to extend their toolbox of methods and learn some new, powerful and rewarding technique.

The school aims at master and PhD students from the fields of mathematics and computer science as well as students with an interdisciplinary background in computational science applications. Each lecture block will take the participants from the general education level into a small specialization topic to get a first insight into a new subtopic that will help them to extend their knowledge on theory and methods.

The 4EU+ alliance aims to take education to a next, a European level. With its four flagships, the alliance tackles large questions in research that have fundamental impact on our societies and the way we live, learn and develop. Flagship 3, “Transforming science and society: Advancing information, computation and communication” is coordinated by Heidelberg University. Our summer schools are meant to be platforms to get in touch with 4EU+ and to share our vision of modern education.

The school will be held in Heidelberg (Germany). If the situation in regard to COVID-19 makes this impossible, the school will be shifted to a digital format.

Target Audience

Postgraduate students, PhD candidates, postdocs and young researchers:

- from the fields of mathematics and computer science as well as students with an interdisciplinary background in computational science applications.
- Master students from Heidelberg University

Speakers

The 4EU+ school is taught in a series of courses and single lectures by:

- Helle Sørensen, University of Copenhagen
- Filip Sadlo, Heidelberg University
- Ivano Eberini, University of Milan
- Wanda Niemyska, University of Warsaw
- Julien Tierny, Sorbonne University

REGISTRATION REQUIRED / APPLY ONLINE / DEADLINE: JULY 29, 2020

Im Zeitalter des Maschinellen Lernens werden die Fortschritte in den anderen Bereichen der Bildverarbeitung schnell übersehen. Daher wird das 75. Heidelberger Bildverarbeitungsforum die Fortschritte in allen Bereichen der Bildverarbeitungsalgorithmik vorstellen mit Fokus auf das Zusammenwirken von allen Komponenten, da ein Kette nur so stark ist wie ihr schwächstes Glied. Ein weiterer Schwerpunkt ist die Frage, wie Lernverfahren praxistauglich und zuverlässig - in anderen Worten mathematisch fundiert - werden können.

Erstmals wird das Forum online stattfinden. Alle geschätzten Merkmale des Forums bleiben erhalten oder werden sogar noch besser: von einem virtuellen Gastgeber passend zum Schwerpunktthema, den man besser kennen lernen kann, hochqualitativen Vorträgen mit Diskussion bis zu einer virtuellen Ausstellung, die Gespräche mit den Ausstellern der Exponate ermöglicht. Hier gibt es eine wichtige Änderung, um das Forum zielgerechter durchzuführen: alle virtuellen Exponate sollten auf das Schwerpunktthema abgestimmt sein.

Durch die Online-Veranstaltung sparen alle Teilnehmer Zeit und Kosten für die Anreise und können die aufgezeichneten Vorträge auch noch nachträglich hören. Ausstellern bietet das Forum in Zeiten ausgefallener Messen die einmalige Gelegenheit genau der richtigen und interessierten Zielgruppe ihre zum Schwerpunktthema passenden Neuentwicklungen vorzustellen. Genauere Angaben zu den Möglichkeiten der virtuellen Ausstellung finden Aussteller auf der Anmeldeseite des Forums.

3D-Vermessung von Objekten zur Neukonzeption der Antikensammlung
Fächerübergreifender Kompetenzkurs (FÜK) mit 2 SWS bzw. 3 LP / ECTS.
Neue Technologien aus dem Bereich der 3D Computer Vision bieten zunehmende Möglichkeiten zur Erfassung, Dokumentation und Analyse von Objekten. Damit entstehen neue Forschungsfragen im interdisziplinären Spannungsfeld zwischen Archäologie und angewandter Informatik. In der praktischen Übung werden originale Objekte der Antikensammlung (https://www.uni-heidelberg.de/fakultaeten/philosophie/zaw/klarch/antikensammlung/ antikensammlung.html) mit einem industriellen hoch-auflösenden opitschen 3D-Scanner erfasst und die 3D-Daten anschließend verarbeitet. Die TeilnehmerInnen erhalten eine Einführung in die optische 3D- Messtechnik; dazu gehört die anschließende Datenverarbeitung mit OptoCAT als Bestandteil des 3D- Scanners und mit dem frei verfügbaren GigaMesh Software Framework (https://gigamesh.eu). Nach dieser Einführung können sie selbstständig in Zweier-Gruppen antike Objekte verschiedener Beschaffenheit mit optischen Verfahren vermessen. Die Daten können soweit verarbeitet werden, dass sie z.B. in einem DataVerse (https://heidata.uni-heidelberg.de/dataverse/iwrgraphics) nachhaltig publiziert werden bzw. als Vorarbeit für z. B. einen CVA Band in Form von Ansichten, Profilschnitten und Abrollungen dienen könnten (CVA Beiheft Wien 1: https://austriaca.at/7145-4inhalt?frames=yes). Die Ergebnisse sollen am Ende der Übung von jeder Zweier-Gruppe in digitaler Form als Bild, Video und interaktiv im Web (http://3dhop.net) präsentiert werden um damit die Eigenschaften und Möglichkeiten der 3D-Messtechnik, Computer Vision und Computergraphik für die Forschung im Umfeld der Archäoinformatik (digital bzw. computational archaeology) zu zeigen.
Arbeitsort: Interdisziplinäres Zentrum für wissenschaftliches Rechnen (IWR) im Neuenheimer Feld 205 (Mathematikon), 5.OG, sowie Antikensammlung (Marstallhof 4).
Die 3D-Vermessung der Objekte finden in Zweiergruppen statt, die ihre Zeit selbst einteilen. Wünschenswert sind interdisziplinäre Gruppen bestehend aus Studierenden der Archäologie und der Informatik.
Termine und Teilnahme:
Vorbesprechung und Vorstellung: Montag, 27. April, 14-16oo, Antikensammlung (Marstallhof 4). Die weiteren Termine mit den Zweier-Gruppen werden individuell vereinbart.
Auf Grund des limiterten Zugang zu dem 3D-Labor/Messtechnik und der Sammlung wird die Teilnehmerzahl beschränkt. Ihre Bewerbung für die Teilnahme senden Sie mit dem dem Betreff „[3DFUEK] Teilnahme“ bis spätestens 20. April an hubert.mara@iwr.uni-heidelberg.de
Siehe auch:
Vorgängerveranstaltung: Praktische Übung: 3-D-Scanning im SS19

Es besteht die Möglichkeit zur Anrechnung in der Archäologie.

!!! Veranstaltung ist auf unbestimmte Zeit verschoben !!!

Die Aufnahme, Speicherung und Weitergabe großer Mengen von Daten ist eine Aufgabe, der sich menschliche Gesellschaften bereits seit Jahrtausenden zu stellen haben. Einen der größten Meilensteine bildet dabei die Erfindung der Schrift, zuerst nachweisbar im Mesopotamien des 4. vorchristlichen Jahrtausends. Zeugnisse dieses Quantensprungs finden sich unter anderem in der Heidelberger Uruk-Warka-Sammlung, die spektakuläre Funde aus dem Sitz des mythischen Königs Gilgamesch bewahrt. Diese Objekte zeugen jedoch nicht nur von den Leistungen antiker Archivare, sie stellen auch eine Herausforderung für ihre modernen Nachfolger dar. Mit welchen Methoden lassen sich archäologische Daten heute sammeln, bewahren und austauschen?

Antworten darauf liefert das Heidelberger "Forensic Computational Geometry Labratory" (FCGL), an dem Methoden zur Digitalisierung archäologischer Artefakte entwickelt werden. Mittels eines Laserscanners werden die Objekte aufgenommen und über das Programm Gigamesh in digitale 3D-Modelle umgesetzt. Unter anderem kommt dieses Verfahren im Projekt "Scanning for Syria" zum Einsatz, in dessen Zentrum die Sicherung von durch den syrischen Bürgerkrieg bedrohten Kulturgütern steht. Das HAIlight im März bietet Ihnen die Gelegenheit, den Forschern am FCGL bei ihrer Arbeit mit Objekten der Uruk-Warka-Sammlung über die Schulter zu schauen.

Das HAIlight findet am Freitag, den 27.03.2020 um 18:00 Uhr statt und dauert ca. eineinhalb bis zwei Stunden. Die Plätze für die Teilnahme sind begrenzt und werden nach Ablauf der Rückmeldefrist verlost. Details zu Treffpunkt und Veranstaltungsort erhalten Sie in der Teilnahmebestätigung.

Für die Platzvergabe schicken Sie uns bitte bis spätestens Montag, 16.03.2020 unter Angabe Ihres Namens eine E-Mail an hailight@alumni.uni-heidelberg.de. Begleitpersonen können dann teilnehmen, wenn nach Berücksichtigung aller interessierten HAI-Mitglieder noch freie Plätze zur Verfügung stehen. Geben Sie daher bitte auch an, ob es sich bei Ihrer Begleitung um ein Mitglied handelt. Vielen Dank für Ihr Verständnis.

! Postponed until Autumn 2020 !

IIT Guwahati and Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University jointly organise the 2nd RTG Big Data Research Summer School 2020. The event will take place from March 23–27, 2020 at one of the most prestigious institutes in in India — IIT Guwahati. The summer school is aimed at advanced master students and PhD students with a background in scientific computing and mathematics.

Renowned experts will hold lectures and seminars on up to date topics and state of the art methods in big data computing and mathematics. The speakers will be researchers predominately from India and Heidelberg University, Germany. Participating students will actively discuss with the experts, solve problems during workshop sessions and some will have the opportunity to present their own research. This provides unique opportunities to the students to hone their skills.

Talk - "Mathematics of Life" Special Interest Group

Climate change, increasing human mobility and trade, pathogen evolution and resistance, urbanization, and ecological range shifts - all these global factors destabilize the current pattern of infectious diseases, notably those transmitted by vectors. There is general agreement that this will lead to the emergence and re-emergence of a wide range of infectious diseases. In Europe, water and vector-borne diseases such as Vibriosis, Dengue, Chikungunya, West Nile Virus, Lyme disease and Tick-borne encephalitis are proliferating and emerging among previously immunologically naive populations. This may result in severe disease outbreaks, morbidity, mortality, long-term disability and increasing burdens of disease. In Low-and-Middle-Income Countries (LMICs), Ebola has not yet been contained, malaria, Dengue and cholera are still associated with massive disease burdens, and arboviruses are likewise on the rise. Globally, resistance to antibiotics and insecticides is a growing concern. New genotypes and new pathogens are threatening to unleash pandemics with potential to have major societal impact, if not effectively monitored and controlled. The recent Corona virus situation is a good example of how sensitive the global population is to local emergence of viruses with epidemic potential. Achieving the sustainable development goals 2030 requires new methods for monitoring, surveillance and analysis, all of which are key for the deployment of more efficient, timely and strategic prevention.

To address these unprecedented global challenges, the public health professions are called on to develop new approaches and innovative techniques and solutions. We are now entering a world, where increasing availability of high quality, high-dimensional data and advanced computation techniques allow for previously unimaginable levels of precision and granularity with respect to monitoring and forecasting of disease outbreaks, their associated burdens and intervention demands. Digitalization, machine learning and artificial intelligence are still in its infancy in terms of public health applications, but hold great promise for revolutionizing public health decision-making, and for sustaining and safeguarding the global population.

This talk provides a few examples on how data from many different disciplines and domains, including climate, human mobility and social media, can be integrated in machine learning, and help timely risk assessment, better forecasts and support the development of more effective prevention strategies. In the talk I will discuss the methods, findings and give examples of tangible decision tools in the making in collaboration with public health policy makers.

“Mathematics of Life” is a special interest group organized by doctoral students of the HGS MathComp.

In times of global pressure on universities the principle of academic freedom is fiercely debated within and outside academia. But surprisingly few academics and even less students have fundamental knowledge what academic freedom is – and what it is not. Debates and actions are often driven by emotions and subjective feelings about a ”proper university“ instead of well founded information.

In this course, participants will

I. discuss the principle of academic freedom – its history, its juridical status and its formal applicability

II. learn to discern academic freedom and other civil liberties (e.g. open speech, freedom of opinion)

III. understand the complexity of taking action in the face of violations to academic freedom

IV. sharpen our awareness for threats to academic freedom in our own societies.

The course material is in English and discussions will be a mixture of English and German (summaries in English will be possible). We expect engagement and interest – no marks will be given!


The course will be held in consecutive blocks. *Friday sessions* are compulsory (course of one hour/1 stündig), Saturday sessions are optional (course of two hours/2-stündig).

he course will take place in the conference room of Marsilius-Kollleg, Im Neuenheimer Feld 130.1


· *Friday, January 29**^th, **, 10 am – 5 pm */(compulsory)/

· *Friday, February 12**^th, **, 10 am – 5 pm */(compulsory)/

· Saturday, February 13^th, , 10 am – 5 pm

· *Friday, February 19**^th, **, 10 am – 5 pm */(compulsory)/

· Saturday, February 20^th, , 10 am – 5 pm

For participation and any queries, please contact thomas.meier@zaw.uni-heidelberg.de *before January 15**^th *!

/Due to Corona-restrictions the number of participants is limited to 15, so please sign up //*soon*//if you are keen to participate./

IWR Colloquium & HGS MathComp Von Neumann Lecture

A traditional goal of algorithmic optimality, squeezing out flops, has been superseded because of evolution in architecture. Flops no longer serve as a reasonable proxy for all aspects of complexity. Instead, algorithms must now squeeze memory, data transfers, and synchronizations, while extra flops on locally cached data represent only small costs in time and energy. Hierarchically low-rank matrices realize a rarely achieved combination of optimal storage complexity and high-computational intensity in approximating a wide class of formally dense linear operators that arise in applications for which exascale computers are being constructed. They may be regarded as algebraic generalizations of the fast multipole method. Methods based on these hierarchical data structures and their simpler cousins, tile low-rank matrices, are well proportioned for early exascale computer architectures, which are provisioned for high processing power relative to memory capacity and memory bandwidth. Hierarchically low-rank matrices are ushering in a renaissance of computational linear algebra. A challenge is that emerging hardware architecture possesses hierarchies of its own that do not generally align with those of a given algorithm-application pair. We describe modules of a software toolkit, hierarchical computations on manycore architectures (HiCMA), that illustrate these features and are intended as building blocks of applications, such as matrix-free higher-order methods in optimization and large-scale spatial statistics. Some modules of this open-source project have been adopted in the software libraries of major vendors.

Biography:

David Keyes directs the Extreme Computing Research Center at the King Abdullah University of Science and Technology (KAUST), where he was the founding Dean of the Division of Mathematical and Computer Sciences and Engineering in 2009 and currently serves in the Office of the President as Senior Associate for strategic priorities and institutional partnerships.

He works at the interface between parallel computing and partial differential equations and statistics, with a current focus on scalable algorithms exploiting data sparsity.

Before joining KAUST he led multi-institutional scalable solver software projects in the SciDAC and ASCI programs of the US DOE, ran university collaboration programs at US Department of Energy and NASA academic collaboration institutes, and taught at Columbia, Old Dominion, and Yale Universities.

He is a Fellow of SIAM, AMS, and AAAS, and has been awarded the ACM Gordon Bell Prize, the IEEE Sidney Fernbach Award, and the SIAM Prize for Distinguished Service to the Profession.

He earned a BSE in Aerospace and Mechanical Sciences from Princeton in 1978 and a PhD in Applied Mathematics from Harvard in 1984.
For more see the abstract_file:

Many of the most relevant observables of matter depend explicitly on atomistic and electronic details, rendering a first principles approach to computational materials design mandatory. Alas, even when using high-performance computers, brute force high-throughput screening of material candidates is beyond any capacity for all but the simplest systems and properties due to the combinatorial nature of chemical compound space, i.e. all the compositional, constitutional, and conformational isomers. Consequently, efficient exploration algorithms exploit implicit redundancies and correlations. I will discuss recently developed statistical learning based approaches for interpolating quantum mechanical observables throughout chemical compound space. Numerical results indicate remarkable performance in terms of efficiency, accuracy, scalability and transferability.
For more see the abstract_file:

For more see the abstract_file:

The Prelude: Pioneering the Development of Conservation Technology in Cambodia

The Sequel: Pioneering the Use of Digital Technology in Banteay Chhmar with the IWR, Heidelberg University

John Sanday who is a Conservation Architect, has spent the last 45 years working in Asia. For at least 15 of these years he has worked in Cambodia. Arriving for the first time in Siem Reap in 1989, John and his team pioneered one of the first projects in Angkor - the Preah Khan Conservation Training Project which was supported by the World Monuments Fund. John’s early memories were of the Khmer Rouge skirmishes which were still taking place on the outskirts of the historic city of Angkor – it was a memorable start to several decades of work in one of the greatest monumental cities of its time, which was placed on the UNESCO World Heritage List in 1992.

In the first part of his talk, John will describe his early days of setting up the first major conservation-training programme in the 12th Century Buddhist monastic complex of Preah Khan. He will talk about some of the problems they had to face and the techniques developed in Preah Khan and three other sites in Angkor. There will be illustrations showing Angkor as John found it in the 1990’s and it will set the background for him to side track to another major Khmer site in the far North of Cambodia.

John will dedicate the second half of his talk to one of the lesser known but highly significant Khmer sites known as Banteay Chhmar, which is closely linked to Angkor. This 12th Century Buddhist, monastic complex stylistically emulates the temples in Angkor and belongs to the Bayon period. Banteay Chhmar became John´s link with IWR and its team. John and Hans Georg Bock had been fantasizing for many years on trying to link heritage conservation with applied mathematics. Here in Banteay Chhmar, they initiated an extraordinary project and a way of using ‘state of the art’ technology to digitally reconstruct iconic face tower as well as sections of the enclosure wall with its exquisite bas-relief carvings. Precise dimensions of hundreds of stone blocks were recorded digitally to recreate the tower, which had to be dismantled and rebuilt, as well as the fallen stones of the bas relief as the first step to their reconstruction.

Khmer architect Dr. Pheakdey Nguonphan (Royal University of Phnom Penh) and Dr. Anja Schäfer (IWR) developed the digital technology and formed a multi-disciplinary research team including stone masons from Preah Khan. John will describe the system, that was developed to solve “John’s Puzzle” and illustrate how the stones began to recognize their original positions in the structures, without having to move the stones manually.

There will be time for questions and discussion at the end.

! Meet & Greet: 13:40, Mathematikon, Common Room, 5th Floor !

Industry’s demand for using big data analysis tools is growing evermore. Public clouds developed in recent years have provided various data analysis tools for analysts, data scientists, researchers, and academics without the burden of permanently allocating and continuously maintaining high performance computing facilities. Google Cloud Platform (GCP) is one of the public cloud providers with a variety of state-of-the-art products addressing wide range of challenges in data engineering and data analytics.
The internet age and growth of social networks was a game changer for human sciences. If previously researchers and analysts had to carefully design data collection processes, now people are sharing their thoughts and concerns on a daily (or hourly) basis. In this workshop we are going to introduce GCP pipelines from streaming Twitter API’s data into a data warehouse. Afterwards, we will perform sentiment analysis and network analysis to find the patterns in user’s behavior. Finally, using visualization tools in python, we will prepare effective communication of the results.

Target Group:

- Students majoring in economics,
information systems and natural sciences.

Hardware/ Software Requirements (Student):

- Laptop

- Anaconda

installation instructions:
https://docs.anaconda.com/anaconda/install

- A google account

Please register here

The students
Understand the process of Business Model Innovation to bring an idea to a monetizable business level including a financial planning. To execute and implement business ideas through Business Development using methods like Value Proposition Canvas, Business Model Canvas, Strategic Innovation Canvas and through Business Analysis using methods like SWOT, PEST and Balanced Scorecard.
Understand techniques for business problem-solving in the areas of ideation, prototyping and testing. Ideation based on problem definition, following rapid prototyping using different tools like LEGO, 3D-Printing and Software Mock Ups, and to get feedback through testing like split tests and iterative customer interviews.
Understand how to present a business idea to motivate customers, supporters, multiplicators, partners and investors through a meaningful pitch deck and agile business plan. An understanding of the framework EXIST Idea Paper will help to apply for potential future funding.
Understand user-centric problem identification such as Design Thinking. Observation of customer needs through interviews and persona creation as well as point-of-view definitions will help to prioritize relevant problem fields.
Understand the basic principles of machine learning and computer vision, such as deep neural networks, necessary to launch a start-up as a business person.
Understand the high-level concepts of the different fields of machine learning, such as reinforcement learning, active learning, supervised and unsupervised learning.
Understand the state-of-the art of computer vision and machine learning, such as object recognition and motion estimation, in order to create ideas for a business model.
Understand the application and connection of machine learning and computer vision techniques to related fields such as hardware design, camera design, robotics, medicine and biology.

Content:
What is the way from identifying a potential market need, until planning and executing a business idea in the area of AI?
This course is split in four parts:

a) Technical part. Short introduction to machine learning. Discussing the different areas in AI, especially machine learning and computer vision, such as deep neural networks, reinforcement learning, active learning, and unsupervised learning. Presenting the state of the art in computer vision and machine learning, such as object recognition, motion estimation, and domain adaption. State of the art in hardware design especially camera design. Discussing the connection of Machine learning and computer vision with related fields such as biology, medicine and robotics.
b) Business part. This part will provide the development from problem to solution using Design Thinking bridging to Business Model Innovation where the idea is formed, streamlined and scaled into a monetizable business idea. We will cover elements like Elevator Pitch, Story Telling, Team Introduction, Business Model (Core Business including Value Proposition, Customer Segment, Customer Relationship and Channels combined with Key Partners, Key Activities and Key Recourses as well as Revenue Streams and Cost Structure), Competition, Market Entry and Closing with Call-to-Action will be processed during the course.
c) We will Invite AI-based start-ups to talk about their expertise
d) There will hands-on sessions and a final project where you should come up with your own AI-based startup.
The block course is in general characterized by high interactivity and workshop character
Teilnahmevoraussetzungen: none.
Prüfungsmodalitäten: There will be no marks. In order to pass the course, the students must attend the course and pass the practical project.

Useful literature:
- Blank, S. & Dorf, B.: The Startup Owner_s Manual: The Step-By-Step Guide for Building a Great Company, K&S Ranch.
- Lewrick, M. et. al.: The Design Thinking Playbook: Mindful Digital Transformation of Teams, Products, Services, Businesses and Ecosystems, Wiley.
- Osterwalder, A. et. Al.: Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, Wiley.
- Gassmann, O. et. al.: The Business Model Navigator: 55 Models That Will Revolutionize Your Business, Financial Times.
- Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Online Course: https://www.coursera.org/learn/machine-learning.
(Since the field of machine Learning and Computer Vision is moving so rapidly there are no books which cover the latest trends. Good (but older) books are:
- Pattern Recognition and Machine Learning, Christopher Bishop
- Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

https://hci.iwr.uni-heidelberg.de/content/design-your-ai-based-startup

The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer

14:00-15:00 Talk
15:00-15:30 Discussion with the speaker after the talk, coffee will be provided

- Interdisziplinäre Verbindung von Mediävistik und Informatik
- Computergestützte Analyse von Burgen, Urkunden und Landkarten
- Dokumentation basierend auf 3D-Modellen, QGIS und Neo4j
- Neue Methoden für die digitale Bauforschung
- Informationsgewinnung mit Personennetzwerken

Registrierung notwendig!

For more see the abstract_file:

Scrum is an agile framework within which people can address complex adaptive problems, while productively and creatively delivering products. Kanban uses a visual system for managing work as it moves through a process, allowing team members to see the state of every piece of work at any time.

Both of them are agile approaches to project management. Agile project management is one answer to the growing speed in which projects need to be delivered and the realization that many projects are not delivered as originally planned. This is especially true for projects with volatile or unclear requirements at project start.

Concepts like continuous improvement, fast feedback cycles, limiting work in progress and transparency can bring value to teams as well as to individuals.

During this workshop you will learn:

- What is Agile? Get an overview of agile principles, values, techniques and methods
- How to use Kanban for your personal use? Boost your productivity and get things done!
- How can Kanban be introduced to a team? Streamline work between team members and create transparency on status
- How can Scrum be adapted in an academic environment? Use a process framework to improve collaboration and knowledge-sharing between lab members and cut down your fixed meeting times

Program:

9:00-12:00

- Agile introduction - origins, mindset & term definition
- Introduction to Scrum Framework
- Introduction to Kanban
- Applying theory into practice (Part 1)
- Personal Kanban - how to gain focus and transparency in your daily work

13:00-15:15

- Applying theory to practice (Part 2)
- Kanban for teams - lightweight way to introduce an agile method to a team
- LabScrum - a process framework to manage work in academic scientific research

Please register here

In the year 2000, the Clay Mathematics Institute selected seven of the most important open problems in modern mathematics and offered a prize of $1 million for a solution to any of them. Nineteen years on, only one millennium prize problem has been solved. In this talk, Prof. David Silvester will discuss the Navier-Stokes existence and smoothness problem, one of the six remaining unsolved problems.

The Navier-Stokes equations are central to fluid dynamics and its applications to engineering and physics, describing viscous turbulent flow, e.g. of air around an aeroplane wing, weather patterns and blood flow through arteries. Despite the wide-ranging applicability of the Navier-Stokes equations, it is still not known whether they always admit smooth solutions, which contain no unphysical "blow-ups", or singularities.

riting performance-critical software productively is still a
challenging task because performance usually conflicts genericity.
Genericity makes programmers productive as it allows them to separate
their software into components that can be exchanged and reused
independently from each other. To achieve performance however, it is
mandatory to instantiate the code with algorithmic variants and
parameters that stem from the application domain, and tailor the code
towards the target architecture. This requires pervasive changes to
the code that destroy genericity.

In this talk, I advocate programming high-performance code using
partial evaluation and present AnyDSL, a clean-slate programming
system with a simple, annotation-based, online partial evaluator. I
will show that AnyDSL can be used to productively implement
high-performance codes from various different domains in a generic way
map them to different target architectures (CPUs with SIMD units,
GPUs). Thereby, the code generated using AnyDSL achieves a performance
that is in the range of multi man-year, industry-grade,
manually-optimized expert codes and highy-optimized code generated
from domains specific languages.

For more see the abstract_file:

This workshop aims at discussing and devising new and unifying concepts to calculate and understand molecular stresses in complex materials. Such molecular stresses can stem from quantum chemical calculations, atomistic or coarse-grained Molecular Dynamics simulations. They could be inherent to the system, i.e. reflect intrinsic tension or pre-stress, or build up upon applying external mechanical perturbations.

In an informal workshop we will bring together experts from the relevant scientific areas, computational physics, materials science, and biological matter, and will leave room for a few contributed talks from participants as well as many discussions among speakers and participants. There is the possibility to participate in a small practical workshop on force distribution analysis (FDA).

The workshop is completely free of charge.

Please register here

Day 1 (Motivation) 09:00 - 12:00
I. Review of FEM error estimation and adaptivity for elliptic PDEs
II. Adaptive timestepping for parabolic PDES

Day 2 (Spatial adaptivity) 09:00 - 12:00
I. Error reduction estimates; marking strategies; proof of convergence
II. Goal-oriented adaptivity; dual problems; numerical experiments

Day 3 (Parametric enhancement) 09:00 - 12:00
I. Stochastic Galerkin approximation; solver ingredients
II. Combining spatial and parametric adaptivity; numerical experiments

Day 4 (Extensions) 09:00 - 10:00
I. Solutions to exercises; open issues; lessons learned

Tutorial Classes
Students will need to have access to a computer or laptop
with MATLAB or Octave installed. The exercises will be based on
the T-IFISS software package which can be downloaded from
http://www.manchester.ac.uk/ifiss/tifiss.html

The Tools Seminar provides an opportunity for scientists and students to get proficient information about certain tools useful for their study or research and to exchange their experience and knowledge about those tools with colleagues and fellow students. The term "tool" is understood in a broad sense ranging from tools useful when developing software to more general issues like how to give a good presentation. Particularly, the aim of the Tools Seminar is to provide profound information which go beyond the basic concepts that many people might already be familiar with. But each talk will also include at least a short introduction to allow the participants to learn about tools they might not have used before. So, no matter which level of experience you have with the tools presented, you should be able to learn something new in this seminar!


All talks will be in English!


The preliminary schedule and the registration form can be found here. The participation in the seminar is free of charge, but please register using the registration form for organizational reasons if you plan to participate!

Registration form

The IWR School 2019 gives a crash course in machine learning with applications from Natural Sciences and Life Sciences. We target young researchers from Natural Sciences and Life Sciences who want to learn more about machine learning. A background in machine learning is not required. Besides introducing the basic concepts of machine learning, we teach selected topics in more depth, such as deep learning, metric learning, transfer learning, Bayesian inverse problems, and causality. Experts from machine learning, Natural Science and Life Science explain how these machine learning approaches are utilized to solve problems in their respective fields of research.

Target Audience:

Postgraduate students, PhD candidates, postdocs and young researchers:

- from Natural and Life Sciences: Microscopy, Biology, Medical, Physics,…
- with interest in Machine Learning
- Master students from Heidelberg University (core course listed in LSF)

Speakers:

The IWR School 2019 is taught in a series of courses and single lectures by:

- Christoph Lampert, Institute of Science and Technology Austria
- Oliver Stegle, European Bioinformatics Institute
- Robert Scheichl, Heidelberg University
- Dominik Janzing, Max Planck Institute for Intelligent Systems
- Klaus Maier Hein, German Cancer Research Center
- Bjoern Ommer, Heidelberg University
- Ullrich Köthe, Heidelberg University
- Anna Kreshuk, European Molecular Biology Laboratory

For more information please visit the website of the IWR School 2019.

Optimal sequential Bayesian inference, or filtering, for the state of a dynamical system requires solving a partial differential equation. For low-dimensional, smooth systems the finite-volume method is an effective solver that gives estimates that converge to the optimal continuous-time values. We develop this finite-volume filter, and give numerical examples that show that the filter we develop is able to handle multi-modal filtering distributions. For higher-dimensional systems the curse or dimensionality may be overcome by representing density functions by an interpolated tensor train decomposition. We give examples of filtering for continuous-time and discrete-time systems.
For more see the abstract_file:

His short course will cover some first steps in performing computational sample-based inference in inverse problems where the forward map requires solving a PDE (partial differential equation). We will look at some MCMC (Markov chain Monte Carlo) algorithms for drawing samples that are distributed according to the resulting posterior distribution, in few and many dimensions, from simple to state of the art. We will also introduce some basic PDE solvers, and discuss the important finite-rank property of the associated forward map. In the last lecture we will discuss mid-level and high-level models, that are the future of this field. The accompanying practical computer sessions allows participants to get hands-on experience with all these topics.

Please register here

For more see the abstract_file:

Computational modeling has become more and more important in the life sciences. One important class of models are compartment models and ordinary differential equations are widely used to describe the time evolution of the model components in a deterministic way. This compact course will introduce stochastic compartmental modeling. The objectives of the course are to learn a) methods that allow to simulate stochastic models and b) which effects so called intrinsic stochasticity can have on systems dynamics. These effects will make it evident that specific calibration techniques are needed in order to be able to cope with stochastic effects and exploit their information. The course will c) give a flavor of how calibration can be performed. Time will also be devoted to let the participants learn d) when stochastic modeling is necessary and beneficial.
This course will consist of lectures as well as practical exercises. Therefore, participants are encouraged to bring laptops (please contact me in case laptop sharing is desired). There is no prior software or programming experience necessary.


Please register here

Scientific computing concerns the development of mathematical models and high-performance software able to describe, simulate and learn the behaviour of complex phenomena. Applications can arise from any area of applied sciences (e.g. engineering, physics, biology, chemistry) and typically retain the challenging task of quantifying high-dimensional uncertainty due to known unknowns and unknown unknowns present in the natural system. When this is added to the computational burden of approximating and solving complex mathematical models, the application of standard inference algorithms, e.g. for parameter estimation, prediction or optimization, becomes quickly unfeasible within a reasonable computational budget.

The aim of the workshop is to bring together researchers working in Uncertainty Quantification, Machine Learning and Bayesian Statistics with a particular focus on high- and infinite-dimensional problems from scientific computing, where the sparsity or uncertainty of data requires an integration of inference and learning algorithms with established physical models, such as partial differential equations. Advances in this complex field of research require a concerted effort from many disciplines, which we hope to foster at the workshop.

This workshop is part of the Thematic Semester Uncertainty Quantification, Machine Learning & Bayesian Statistics in Scientific Computing at MAThematics Center Heidelberg (MATCH) in conjunction with the Excellence Cluster STRUCTURES. The financial support from MATCH and from the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (HGS MathComp) is gratefully acknowledged.

Registration required!

For more see the abstract_file:

09:00 Uhr
"Guided Parameter Exploration in Interactive Visualization"
Prof. Stefan Bruckner, University of Bergen, Norway

Over the past decades the field of visualization has firmly established itself as an important and constantly expanding discipline within computer science. Computer-based visualization seeks to provide interactive graphical data representations, taking advantage of the extraordinary capability of the human brain to process visual information. Advanced visualization methods now play an important role in the exploration, analysis, and presentation of data in many fields such as medicine, biology, geology, or engineering. This development, however, has also lead to the fact that there is now a vast number of often very specialized techniques to visualize different types of data tailored towards specific tasks. Hence, particularly for non-experts, it becomes increasingly difficult to choose appropriate methods that will provide the optimal answers to their questions.

In this talk, I will discuss previous and ongoing research on how we can explore and navigate the space of visualizations itself. By consider the interplay between data, visualization algorithms, their parameters, perception, and cognition as a complex phenomenon that deserves study in its own right, we are making progress in providing goal-oriented interfaces for visual analysis. For instance, we can make the modification of input parameters of visualization algorithms more intuitive by normalizing their perceived effects over the entire value range, and provide visual guidance about their influence. Furthermore, by incorporating additional knowledge into the visualization process, we can infer information about the goals of a user, and develop smarter systems that automatically suggest appropriate visualization techniques. This line of investigation leads us along the path towards a new type of visual data science, where automated data analysis approaches such as deep learning are tightly coupled with interactive visualization techniques to exploit their complementary advantages for knowledge discovery in data-driven science.

10:00 Uhr
"Topological and Morphological Analysis of Flow Fields and Beyond"
Prof. Filip Sadlo, Universität Heidelberg

This talk focuses on four active branches in scientific visualization research: topological analysis, feature extraction, volume rendering, and solver visualization. We examine various roles of topological analysis in flow fields and beyond, we investigate feature extraction in higher dimensions and higher order, we extend volume rendering beyond direct geometrical optics, and we extend scientific visualization from the traditional analysis of simulated data to analysis of the numerical solvers that produce the data. On the application side, we discuss the utility of the investigated visualization techniques in the natural and life sciences, and indicate possible directions of future research.

11:00 Uhr
"Insights from the Pixel Dump: Scientific Image Visualization"
Prof. Thomas Schulz, Universität Bonn

Big, complex, and dynamic image data play an increasing role in science and medicine. This poses important and interesting challenges to scientific visualization, since the traditional visual inspection of raw images is no longer a suitable strategy for their effective and efficient interpretation. Instead, mathematical modeling, feature extraction, and machine learning are required to pre-process the data, and to allow the human user to reason about it at a higher level of abstraction. This talk will illustrate these points with several specific examples from diffusion Magnetic Resonance Imaging, as well as image data from ophthalmic epidemiology.

For more see the abstract_file:

Recent years have seen intense development of discretization schemes for incompressible flow problems in two directions. On the one hand, pairs of discrete spaces with a commuting diagram property for the divergence operator have been developed, with the result that it is now possible to compute actually divergence free solutions with reasonable effort. In particular for high Reynolds number flow, this property is important, since the control of the divergence by the gradient is too weak. Alternatively, penalization of the divergence has been investigated thoroughly with the same goal of achieving better solutions for high Reynolds numbers. On the other hand, replacements for the pressure Poisson problem have been developed, allowing for much faster projection of approximate solutions into the divergence free subspace, in particular with high performance computing in mind. The study of stability of such flows and of critical modes requires the solution of nonsymmetric variational eigenvalue problems. Critical modes are characterized by eigenvalues with small real part, which again may suffer from spurious divergence. In order to approximate such eigenvalues, many flow problems must be solved iteratively, which brings fast solvers back into the game.

The goal of this workshop is convening top researchers in the fields of flow and eigenvalue problems in order to understand the interplay of the interacting components better and to profit from recent research of groups with different focus. Furthermore, its aim is intensifying cooperation between the members of PIMS and universities in Germany with a clear focus on common interest.

This mini-workshop will bring together experts in modeling and analysis of organizing principles of multiscale biological systems such as cell assemblies, tissues and populations, and collective dynamics of cells. We will focus on questions arising in systems biology and medicine which are related to emergence, function and control of spatial structures, cell-cell interactions, and inter-individual heterogeneity in biological dynamics. Mechanisms of symmetry breaking and establishment of spatial patterns in gene expression leading to different differentiation programmes are central issues of developmental biology, while the understanding of their perturbation and deregulation leading to abnormal development is important in cancer research. Evolution of large scale spatial patches such as, for example, systems of vegetation patterns observed in drylands, is essential for ecosystems. Dynamics of appearance and disappearance of such patterns have a direct economic impact. Spatio-temporal dynamics arising through a diffusion field is also a central theme in characterizing the collective response of microbial particles.

Pattern formation is also an important topic in materials science. For example, the nature of formation and evolution of nano-scale structures in energy conversion devices such as fuel cells and solar cells is decisive for the quality of the performance of these devices. Though some of these patterns are well characterized, there are other that we are only beginning to understand. Mathematical modeling is a powerful technique to address key questions and paradigms in diverse model systems and to provide quantitative insights into the role of the nonlinear and nonlocal interactions within the systems and with the external fields as well as of the growth and transport processes and their impact on the observed patterns.
Although applied to specific biological, ecological, chemical, medical or physical systems, mathematical models allow for a comparative analysis of design principles in diverse systems. The focus of this proposed conference is to present and analyze models of partial and integro-differential equations applied to problems of spatio-temporal patterning. The goal of the meeting is to bring together specialists in Germany and from PIMS universities working on different aspects of the field, including mathematical modeling and applications, analysis of the underlying equations as well as numerical simulation, in order to exchange ideas, present new techniques, and identify challenging new research directions of common interest. The focus will be in identifying and understanding of mechanisms of pattern formation including formation of travelling waves, stationary and dynamical patterns, the effect of mechanical-chemical forces on patterns, stability and bifurcation theory, mechanisms underlying collective dynamics in cell signalling, and the emergence of singularities. Applications to developmental biology, ecology, cell-signalling, and materials science will be presented and discussed.

The outcome of the workshop will be two-fold. Firstly, various mathematical methods and techniques presented for diverse types of model PDE sytems in biology, will lead to cross-fertilization and will help solving in tackling problems related to different applications. Secondly, this workshop will identify common research interests and establish new research collaborations on specific projects among researchers at PIMS and at Universities in Heidelberg, Munster and Berlin.

Learning time-series models is useful for many applications, such as simulation and forecasting. In this study, we consider the problem of actively learning time-series models while taking given safety constraints into account. For time-series modeling we employ a Gaussian process with a nonlinear exogenous input structure. The proposed approach generates data appropriate for time series model learning, i.e. input and output trajectories, by dynamically exploring the input space. The approach parameterizes the input trajectory as consecutive trajectory sections, which are determined stepwise given safety requirements and past observations. We analyze the proposed algorithm and evaluate it empirically on a technical application. The results show the effectiveness of our approach in a realistic technical use case.


Afterwards there will be a Meet & Greet with Pizza and Beer (and non-alcoholic beverages)!

For more see the abstract_file:

We consider nonconvex and highly nonlinear mathematical programming problems including finite dimensional nonlinear programming problems as well as optimization problems with partial differential equations and control constraints. We present a novel numerical solution method, which is based on a projected gradient/anti-gradient flow for an augmented Lagrangian on the primal/dual variables. We show that under reasonable assumptions, the nonsmooth flow equations possess uniquely determined global solutions, whose limit points (provided that they exist) are critical, i.e., they satisfy a first-order necessary optimality condition. Under additional mild conditions, a critical point cannot be asymptotically stable if it has an emanating feasible curve along which the objective function decreases. This implies that small perturbations will make the flow escape critical points that are maxima or saddle points. If we apply a projected backward Euler method to the flow, we obtain a semismooth algebraic equation, whose solution can be traced for growing step sizes, e.g., by a continuation method with a local (inexact) semismooth Newton method as a corrector, until a singularity is encountered and the homotopy cannot be extended further. Moreover, the projected backward Euler equations admit an interpretation as necessary optimality conditions of a proximal-type regularization of the original problem. The prox-problems have favorable properties, which guarantee that the prox-problems have uniquely determined primal/dual solutions if the Euler step size is sufficiently small and the augmented Lagrangian parameter is sufficiently large. The prox-problems morph into the original problem when taking the step size to infinity, which allows the following active-set-type sequential homotopy method: From the current iterate, compute a projected backward Euler step by applying either local (inexact) semismooth Newton iterations on the step equations or local (inexact) SQP-type (sequential quadratic programming) methods on the prox-problems. If the homotopy cannot be continued much further, take the current result as a starting point for the next projected backward Euler step. If we can drive the step size all the way to infinity, we can transition to fast local convergence. We can interpret this sequential homotopy method as extensions to several well-known but seemingly unrelated optimization methods: A general globalization method for local inexact semismooth Newton methods and local inexact SQP-type methods, a proximal point algorithm for problems with explicit constraints, and an implicit version of the Arrow--Hurwicz gradient method for convex problems dating back to the 1950s extended to nonconvex problems. We close the talk with numerical results for a class of highly nonlinear and badly conditioned control constrained elliptic optimal control problems with a semismooth Newton approach for the regularized subproblems.

Preprint available on https://arxiv.org/abs/1902.06984

Lung cancer (LC) is the leading cause of death of cancer in Canada in both men and women, and indoor radon is the second leading cause of LC after tobacco smoking. The Population Attributable Risk (PAR) is used to assess radon exposure risk. We use the PAR to identify the radon levels responsible for most LC cases. During the period 2006–2009, 6% of houses in Ontario, 9% of houses in Alberta, 19% of houses in Manitoba, 7% of houses in Quebec, and 5% of houses in British Columbia had radon levels higher than 200 Bq/m3 and was responsible about 913, 211, 260, 972, and 258 lives, respectively. Radon mitigation programs could have prevented these LC cases. We use the PAR function of the two variables, radon action, and target levels, to search for a possible optimal mitigation program. The PAR is a linear function in the target radon value with an estimated slope of 0.0001 for Ontario, Alberta, Quebec, and British Columbia, and 0.0004 for Manitoba. The PAR is an increasing function in the radon action level. The PAR is sensitive to changes in the radon mitigation program and as such, any improvement is a worthwhile investment.

[1] Al-arydah, M. (2018). Estimating the Burden of Lung Cancer and the
Efficiency of Home Radon Mitigation Systems in some Canadian Provinces.
Science of the Total Environment, 626, , 287-306.
[2] Al-arydah, M. (2017). Population attributable risk associated with lung
cancer induced by residential radon in Canada. Sensitivity to relative risk mo-
del and radon. Science of the Total Environment. http://dx.doi.org/10.1016/j.scitotenv.2017.04.067.

Organizers:
Katharina Anders, Bernhard Höfle, Hubert Mara

Compact Course & Workshop:
- Automatic methods for 3D geospatial data processing
- Geographic applications of 3D data analysis
- Hands-on: 3D point cloud and mesh analysis
- Programming and research challenge: Development of computational methods for 3D information extraction

Invited speakers:
- Prof. Dr. Andreas Nüchter, University of Würzburg
- Jorge Martínez Sánchez, University of Santiago de Compostela

Registration:
Please register on the website of the Compact Course until February 15, 2019
www.uni-heidelberg.de/stap19

Project Auto3Dscapes:
www.uni-heidelberg.de/auto3Dscapes

Contact: Katharina Anders
katharina.anders@uni-heidelberg.de

Twitter:
#STAP19

Tidy data is a standard way of storing your data where columns are variables and rows are observations. Tidy data, particularly when coupled with tidy tools, makes data analysis easier because you can spend less time wrangling the output of one function so that it works as the input for another. Tidy data will make your analysis easier but how you get wild-caught data into a tidy form? In this talk, I`ll discuss some of the tools that I have worked on for tidying data (e.g. the tidyr package), the limitations of those tools, and what I`m thinking about next. In particular, I`ll discuss a new approach for "pivoting" data, and discuss some of the challenges posed by data stored in hierarchical form (e.g. JSON).

Biography:

Hadley Wickham has pioneered the development of advanced data visualisation and analysis approaches for the R statistical computing platform. He holds a BSc. in Human Biology, and a BSc. and MSc. in Statistics from the University of Auckland. He went on to work with Di Cook and Heike Hofmann at Iowa State University, and obtained his PhD in 2008. In 2007, Hadley released ggplot2 - a data visualisation library based on Leland Wilkinson`s "The Grammar of Graphics", and in 2013, unveiled "The Tidyverse" - a collection of libraries and methodological approaches for the efficient manipulation of complex data in R. His contributions to the field were recognised in 2008, with his receipt of the John Chambers Award for Statisical Computing, and in 2015, he was made a fellow of the American Statistical Computing Association.

Educational qualifications:
BSc. Human Biology, U. Auckland, NZ.
BSc. MSc. Statistics, U. Auckland, NZ.
PhD Statistics, Iowa State U., USA.

Professional Awards:
2008. John Chambers Award for Statistical Computing
2015. Fellow of the American Statistical Association

The event is organized in close cooperation with the conference "Geometric Analysis meets Geometric Topology“.

Description:

This touring exhibition, whose starting point is the 7th ECM held in July 2016 in Berlin, stems from the observation that nowadays, women still find it difficult to embrace a career in the mathematical academic world and the disparity between the proportion of men and that of women among professional mathematicians is still shamefully large.

The thirteen women mathematicians portrayed here share with us their experience, thus serving as role models to stimulate young women scientists to trust their own strength. In presenting mathematics through women mathematicians’ perspectives and samples of their life stories, we hope to highlight the human aspects of producing mathematics, making this discipline more tangible and therefore more accessible to outsiders or newcomers.

This exhibition and the catalogue (publishing house: Verlag am Fluss) are the result of the joint efforts of the photographer Noel Tovia Matoff and four mathematicians by Sylvie Paycha, Sara Azzali, Alexandra Antoniouk, Magdalena Georgescu, with the precious help of Maria Hoffmann-Dartevelle, who translated into German and Sara Munday, who proofread the interviews and, last but not least, our two inspired graphic designers Wenke Neunast/eckedesign (exhibition) and Gesine Krüger (catalogue).

Link Exhibition

The event is kindly supported by the Heidelberg Laureate Forum Foundation (HLFF).

The exhibition will be on display from February 26 - May 31, 2019 at the Foyer of the Mathematikon.

Dr. Maarten J. Bijlsma is an epidemiologist and applied statistician primarily interested in applying counterfactual causal inference methods to study population health, mortality, and fertility. Methodologically, he is currently focusing on the parametric g-formula, which is a very flexible method for modelling dynamic longitudinal relationships. Substantively, he is investigating how socio-economic determinants interact with both physical and mental health over the life course. He holds an MSc degree in Applied Statistics from the University of Ghent (Belgium), an MSc degree in Demography and a PhD in Epidemiology from the University of Groningen (the Netherlands). He is currently employed as a Research Scientist at the Max Planck Institute for Demographic Research in Rostock, Germany.

Working as a PhD student you have the challenging task of developing research findings and write you doctoral thesis within three years. This alone is a demanding job. In addition, it is vital to the scientific process that your findings are presented to the scientific community. For most PhD students this is the first big project in their professional life and it could have a crucial impact on their future professional career. PhD students are highly motivated when they start their PhD studies but may underestimate the need for professional management for this three-year project "doctoral thesis".
This seminar demonstrates how to approach the doctoral thesis in a professional way. Project management tools and techniques are used, tailored to the specific situation of PhD students. You will learn how to set a project vision, define clear objectives, gain buy-in from your supervisor and other colleagues in your group, and how to develop a project plan, which is structured and at the same time flexible enough to easily adjust to unexpected findings. You will establish a "controlling cycle" which helps you to recognise risks and problems as early as possible, and you will learn how to manage critical situations and deal with ups and downs. Furthermore, networking with colleagues, supervisors and other people are important topics of this seminar.
Throughout the seminar, you will work on your own doctoral thesis and share your experience with others. This seminar is most beneficial for PhD students who are in the early phases of their doctoral thesis. At the end of the seminar you will have established a strategy on how to approach your own doctoral thesis. During the follow-up REVIEW we will share experience and best practices and deal with open questions from the first module.
This seminar will help you to make the most effective use of your three years and finish your doctoral thesis on time.
You will also learn and practise the basic concepts of project management – a prerequisite in industries and research institutions.

Please register here:
https://hgs.iwr.uni-heidelberg.de/Portfolio_HGS/VERANSTALTUNGEN/reg_form/reg_form.php?id=228

Organizers: Frauke Gräter and Lipi Thukral

This workshop will focus on new developments in the area of membrane biology using molecular dynamics simulations and integrative computational techniques. The workshop will broadly cover themes specific to membrane signaling, membrane mechanics, and recent trends in integrating experimental data into computational structure and function that will aid in the prediction of proteins in/at membranes.

Registration required!

For more see the abstract_file:

Moderne Materialien zählen zu den zentralen Zukunftsthemen in der angewandten Forschung. Die Verwendung hochmoderner Planungsprozesse in den Materialwissenschaften und bahnbrechende Entdeckungen in der Nanoforschung, in der organischen Elektronik und in der computergestützten theoretischen Chemie haben zu einer Revolution geführt. Als eine der Schlüsseltechnologien für das 21. Jahrhundert erlauben die Modernen Materialien einen zielgerichteten Einsatz in zahlreichen Anwendungsgebieten. Durch die Kombination von mehreren Eigenschaften werden immer effektivere Werkstoffe ermöglicht. So können zum Beispiel Stoffe entwickelt werden, die gleichzeitig extrem leicht aber dennoch stabil sind oder wesentlich effizienteren Energietransport erlauben.

Was ist von der Materialforschung in der nächsten Dekade an Entwicklungen noch zu erwarten? Wie wirken hier die unterschiedlichen Forschungsrichtungen zusammen? Und welche Rolle spielt die computergestützte Simulationstechnik bei diesem Paradigmenwechsel von der experimentellen Entwicklung neuer Materialien zur gezielten Planung von Materialeigenschaften am Computer? Mit diesen Fragen beschäftigt sich der 16. Modellierungstag. Wir haben Experten aus Universitäten, Forschung und Produktion eingeladen, um in Impulsvorträgen und praxisnahen Diskussionen die zentralen Fragestellungen aus diesem interdisziplinären Feld zu erörtern.

Die Veranstaltung wird von HGS MathComp und der Stadt Heidelberg organisiert sowie von der IHK Rhein-Neckar und der Industrie unterstützt.

Die Teilnahme an der Veranstaltung ist nach der Anmeldung kostenfrei. Um Anmeldung bis zum 20. Januar 2019 wird gebeten.

Anmeldung

For more see the abstract_file:

John Sanday, Conservation Architect, who has spent the last 45 years working in Asia, worked for at least 20 of those years in Cambodia. Arriving for the first time in Siem Reap in 1989, he and his team pioneered the first project, the Preah Khan Conservation Training Project which was supported by the World Monuments Fund. The Khmer Rouge disturbances were still evident in Angkor as the fast-growing sub-tropical jungle, which engulfed the partially ruined monuments provided an ideal hiding place for the Khmer Rouge militia. John’s early memories were of the skirmishes still taking place on the outskirts of the historic city of Angkor and the sounds of explosions and gunfire – it was indeed a memorable start to several decades of working in one of the largest monumental cities of its time, which was later to be placed on the UNESCO World Heritage List.
John will briefly describe his early days of setting up the first major conservation training programme in the 12th Century Buddhist monastic complex. As many of you will be able to recall the time we have spent together in Angkor, I will take this opportunity to describe some of the problems we had to face and the techniques we developed in Preah Khan and three other sites in Angkor to conserve the structures with minimal intervention. There will be plenty of illustrations showing Angkor as John found it in the 1990’s and it will provide an excuse and set the background for him to side track to another Khmer style site in the far North of Cambodia.
Banteay Chhmar, one of the great Khmer sites, is closely linked to Angkor despite it being about 100km to its north. This 12th Century site, which is stylistically emulates the temples in Angkor of the Bayon period, is my link with IWR as it was the birth of an extraordinary project which Professor Georg Bock and had been fantasizing for many years trying to link heritage conservation with applied mathematics. We found a way of using ‘start of the art’ technology to digitally reconstruct a section of exquisite bas relief carvings on a stone enclosure wall which enclosed the temple complex known as Banteay Chhmar. This project need careful measurement and digital recreation of the fallen sections as the first step to their reconstruction following a highly sensitive conservation intervention to protect the decorative stone carvings. The Bas Relief Wall measures 1,400 metres in length of which 75% has collapsed.

Similarly, a free-standing sandstone tower supporting four carved images of, possibly the king or maybe the Buddha, measuring approximately 15 metres high, was threatening imminent collapse. These two different architectural elements were selected to test a system for digital re-assembly.

A section of the enclosure wall was selected. Each stone in was measured and referenced. Missing stones were located and the decorative stones were carefully dismantled and each stone was scanned. A process was also developed for the consolidation and cleaning of these masterpieces ready for reconstruction.
Drawings of the Tower were prepared referenced and carefully dismantled and each stone was scanned.
John will describe the system which IWR developed to solve “John’s Puzzle”, Khmer architect Dr. Peakdey Nguonphan and Dr. Ann from Germany headed up the team which developed the digital technology.
As a result of this multi-disciplinary research and along with support from many of the IWR teaching staff, the stones began to recognize their original positions in the structures and along with the knowledge and experience of the Khmer stone masons who had worked with us in Preah Khan, progress was made. I will explain the full process with illustrations.

Time will be allocated for questions ad discussions.

The workshop gives a basic knowledge about:
What is a patent – what is the use of a patent
What is patentable – criteria of the patent examination process
Difference between software copyright and patent
Best practice for patenting your invention

For more see the abstract_file:

Turbulent flames feature a complex multi-scale turbulence and chemistry interaction, which usually leads to the flame structure that cannot be simply categorized into the single-regime burning. The simplest burning structure of flame is in either non-premixed or premixed regime, for which two distinct modes are observed for the species transportation and reactions. However, the combustion processes are further complicated in most practical applications, for example, the liquid-fueled burner that characterizes the additional dispersed phase for fuel supply, and hence the partially premixed reaction as well as an evaporation-dominated regime. This multi-regime combustion mode is therefore more often involved and poses a challenge to the model. In this work, due to the computational efficiency, the conventional flamelet model that is originally proposed for simple premixed or non-premixed reactions is explored for use in large eddy simulation (LES) of multi-regime turbulent flames. The changes of reaction regime at sub-grid scale are dynamically described by a flame index that is developed in a way facilitating the implementation of single-regime flamelet structures. The validity of models is examined by consideration of both gas and liquid flames, which include a lifted jet flame and a piloted spray flame. Results show that although formed by different mechanism, the partially premixed reaction is predominant in the considered flames, and the present model can properly reproduce these structures. Computed data are in general good agreement with experimental profiles of temperature, species mass fraction and droplet size.

Projekte im Bildungs-, Sozial- und im Forschungsbereich dienen dazu, kurz- oder mittelfristig arbeitsplatzsichernd zu wirken und Nachwuchskräften weitere Berufserfahrung und Qualifizierungsmöglichkeiten zu bieten. Aus der Perspektive von wissenschaftlichen Einrichtungen und Hochschulen sind sie zudem erwünscht, um die Drittmittelbilanz zu stärken und somit im nationalen Leistungsvergleich der Hochschulen eine mo?glichst positive Stellung zu erreichen.

Häufig müssen Mitarbeiter/innen von Hochschulen oder Forschungsinstituten ohne entsprechende Vorerfahrung an Projektanträgen arbeiten. Möglichkeiten der hausinternen Unterstützung oder des Austausches mit projekterfahrenen Mitarbeitern/innen sind selten. Dadurch gehen wertvolle Zeit- und Personalressourcen verloren. Dieses Seminar hat deshalb zum Ziel, die Antragstellung stärker zu professionalisieren, Tipps und Tricks zu vermitteln und im Endeffekt eine höhere Erfolgsbilanz zu erzielen.

Im Seminar gehe ich mit Ihnen Schritt für Schritt die wesentlichen Aspekte der Antragsgestaltung durch und erkläre diese an Beispielen. Dabei werden auch einige Grundlagen des Projektmanagements vermittelt. Denn Fehler, die bei der Planung gemacht werden, können später zu schwerwiegenden Folgen im Verlauf des Projektes führen.
In diesem Seminar werden Problemstellungen aufgegriffen wie:
• Wie entwickle ich aus meiner Idee ein perfektes Konzept?
• Antragssprache – Antragsprosa: Einige Schreibtipps
• Wie interpretiere und verstehe ich ein Förderprogramm? Was muss ich beim Antragschreiben unbedingt berücksichtigen?
• Über den Umgang mit Gutachtern: Evaluationsprozesse, Wie wird ein Antrag gelesen? Welche Faktoren führen zu Entscheidungen?
• Wo und wie finde ich Partner und wie binde ich diese in ein Konsortium ein?
• Wie recherchiere ich nach Förderprogrammen?
• Wie passe ich meine Idee an die Vorstellungen des Förderers an?
Da jedes Programm andere Fo?rderbedingungen stellt, werde ich mich auf einige fachspezifisch passende Pro- gramme konzentrieren. Grundbedingungen und Vorgehensweise in der Antragsgestaltung sind jedoch auf alle Förderprogramme übertragbar.
Alle Projektphasen oder wichtige Themen werden in Arbeitsgruppen vertieft. Einige TeilnehmerInnen werden im Seminar Gelegenheit haben, aktiv in Arbeitsgruppen an eigenen Projektantra?gen zu arbeiten und diese mit ent- sprechendem Feedback von mir sowie den anderen TeilnehmerInnen zu einem Grobkonzept zu entwickeln. Nutzen Sie diese Chance! Bringen Sie nach Möglichkeit eine Projektidee mit, die Sie gerne zu einem Antrag ent- wickeln würden. Ich werde vorbereitend vor dem Seminar noch einen Fragebogen versenden um evtl. passende Förderprogramme recherchieren zu können.

1. Tag

*Phase 1: Vorantragsstrategie & Basics*
Das Zeitproblem bei der Antragstellung Strategische Tipps
Pluspunkte im Konzept erlangen
Fehler und Fallen
Die Rolle der Gutachter Antragsprosa - Schreibtipps
Antragstellung Schritt für Schritt Projektideenentwicklung Erstellen einer Kurzskizze

2. Tag

*Phase 2: Förderpolitik & Recherche*
Professionell Projektanträge konzipieren
Programm für zwei Tage
Vom Umgang mit Fördermittelgebern / Förderprogramme
Förderpolitik und Förderphilosophie
Wie interpretiere und verstehe ich ein Förderprogramm? Was muss ich beim Antragschreiben unbedingt berücksichtigen?
Programmrecherche – Wie und wo?
Information über diverse Förderprogramme, je nach Bedarf der Teilnehmenden
*Phase 3: Grobplanungsphase*
Anpassung der Idee an die Förderbestimmungen
Formulare und Bürokratie - Der Horror schlechthin? Der verwaltungstechnische Teil des Antrags Von der Skizze zum Konzept: Die inhaltliche Ausgestaltung des Projektantrages
Weitere Konzeptanpassungen

*Phase 4: Detailplanungsphase*
Projektorganisation: Partner und ihre Rollen im Projekt
Erarbeitung der Projektstruktur: Methoden der Projektplanung als Grundlage des Finanzplans

Bitte hier anmelden

Angebot: Interkulturelles Training (Zielkultur Indien)
Im eintägigen Workshop zur Zielkultur Indien erhalten Teilnehmende die Möglichkeit Ein-blicke in Eigenheiten der indischen Kultur zu erhalten und die Vielfalt der selbigen kennen-zulernen. Gerade im Umgang mit Mitmenschen anderer Kulturen ergeben sich eine Vielzahl von Möglichkeiten für Konflikte und Missverständnisse, die durch einen achtsamen Umgang (auch mit den eigenen Erwartungen) die Zusammenarbeit positiv beeinflussen kann.
Neben Einblicken in die Kultur werden im Workshop auch eigene kulturelle Prägungen ana-lysiert und deren Verallgemeinerbarkeit reflektiert.
Inhalte
* Nationalkultur, Berufskultur oder Familienkultur: Was ist Kultur?
* Einfu?hrung in die indische Kultur
* Kulturdimensionen nach GLOBE und Einordnung der deutschen und indischen Kultur
* Stereotype und Vorurteile: Wie gelingt ein sensibler Umgang?
* Unsicherheitsvermeidung und Kommunikation als zentraler Schlu?ssel zu deutsch-indischer Zusammenarbeit
* Aktives Erwartungsmanagement auf beiden Seiten
* Alltagsbeispiele und Best Practices aus Unternehmen und Universitäten
Methoden
* Kurzvorträge
* Offene und geleitete Diskussion
* Praktische Übungen (einzeln sowie in Gruppen)


Anmeldung: https://hgs.iwr.uni-heidelberg.de/Portfolio_HGS/VERANSTALTUNGEN/reg_form/reg_form.php?id=221

Schedule:

10:00-11:00 Registration and coffee
11:00-12:00 Herbert Edelsbrunner (IST Austria)
12:00-13:30 Lunch
13:30-14:30 Heather Harrington (University of Oxford)
14:30-15:15 Coffee Break
15:15-16:15 Ulrich Bauer (TU München)
16:30-17:30 Egor Shelukin (University of Montreal)

Due to space constraints we ask participants to register for this workshop with name and affiliation at:

persistence@mathi.uni-heidelberg.de

Veranstaltung anlässlich des 60. Geburtstags von Prof. Dr. Eva Gutheil.

Online-Registrierung

Die Teilnahme ist nach Anmeldung kostenfrei.

Veranstaltung anlässlich des 60. Geburtstags von Prof. Dr. Eva Gutheil.

Online-Registrierung

Die Teilnahme ist nach Anmeldung kostenfrei.

Mit der Verfügbarkeit leistungsfähiger Computer und Softwarewerkzeuge hat sich die mathematische Modellierung, Simulation und Optimierung (MSO), als zentrale Methodik des Wissenschaftlichen Rechnens, zu einer Schlüsseltechnologie entwickelt. Aktuelle Ergebnisse der MSO in der Hochschulforschung führen allerdings auf Grund befristeter Projekte oft nur zu prototypischer, nicht nachhaltiger Software. Dieses strukturelle Hindernis führt dazu, dass neue Verfahren ihr großes Potential zur Lösung der immer komplexeren Probleme in Wissenschaft, Industrie und Gesellschaft nur begrenzt entfalten. Mit der Einrichtung des durch die Carl-Zeiss-Stiftung geförderten SCSC sollen am IWR Strukturen geschaffen werden, die dieses Hindernis beseitigen und einen wirksamen Technologietransfer in inner- und außeruniversitäre Anwendungsbereiche ermöglichen.

Der ZUK 5.4 Challenge Workshop „Herausforderungen bei der Analyse von alten Schriften im digitalen Zeitalter", organisiert vom IWR in Zusammenarbeit mit den Akademievorhaben „Altägyptische Kursivschriften“ (Akademie der Wissenschaften und der Literatur, Mainz) und „Textdatenbank und Wörterbuch des Klassischen Maya“ (Nordrhein-Westfälische Akademie der Wissenschaften und der Künste) möchte Schnittmengen zwischen Informatik und Schrift- und Sprachforschern finden, um gemeinsam die Rätsel antiker Texte zu lüften.

- Kann Artificial Intelligence im digitalen Zeitalter das Rätsel alter Schriften und Sprachen knacken? Welche Computeranwendungen und Algorithmen helfen bei der Analyse antiker Schriften?
- Wie sehen die Dokumentationstechnologien von Text und Schrift in 3D und 2D aus?
- Welche neuen Methoden gibt es für die digitale Paläographie?
- Welche Voraussetzungen und Standards sind für die nachhaltige Nutzung notwendig?
- Diesen Fragen geht der interdisziplinäre Workshop mit zahlreichen Experten nach.

Der Workshop ermöglicht Vertretern verschiedener Disziplinen, die sich mit Computeranwendungen und quantitativen Methoden in der Schrift- und Sprachforschung beschäftigen, mehr über laufende Forschungsprojekte oder Abschlussarbeiten zu erfahren sowie über die Möglichkeiten und Grenzen verschiedener Methoden zu diskutieren. Im Mittelpunkt des Workshops steht die Zusammenarbeit zwischen Informatik und Altertumswissenschaften.

Neben Kollegen, Postdoktoranden und Doktoranden sind auch ausdrücklich Studierende, die ihre digitalen Kenntnisse erweitern, bzw. begonnene Arbeiten diskutieren möchten, herzlich willkommen.

! Anmeldung erforderlich ! (Deadline: 15. Oktober 2018)

Soil water movement is a key process in ecosystem services, such as biomass production, fresh water retention, climate regulation, or water buffering and filtering. However, the quantitative description of soil water movement on all relevant scales from meters to the global scale, remains an open challenge. In this talk I focus on the meter scale, where soil water movement can still be described with the process based Richards equation. Nevertheless, the mathematical representation of soil water movement exhibits uncertainties in all model components. This means that the representation of uncertainties in each model component becomes an integral part of the model formulation. The goal is then an optimal consistent representation with minimal uncertainties. Data assimilation methods, which combine models and data, are a key tool for this task. In this talk I present an application on a real-world case. We assessed the key uncertainties for the specific hydraulic situation of a 1-D soil profile with TDR (time domain reflectometry)-measured water contents. We employed a data assimilation method, the ensemble Kalman filter (EnKF), with an augmented state to represent and reduce all key uncertainties (initial condition, soil hydraulic parameters, small-scale heterogeneity, and upper boundary condition), except for an intermittent violation of the local equilibrium assumption by the Richards equation. To bridge this time, we employed a closed-eye period, which pauses the parameter estimation and only guides the states through this time. This ensured constant parameters throughout the whole estimation, suggesting that we achieved a more consistent description and limited the incorporation of errors into parameters.

There are various reasons for studying fixed-point property of non-continuous mappings, e.g., due to errors or perturbations, original mappings lose their contractivity or their continuity, and therefore, the existence of their fixed-points is no more warranted. To counteract this problem, we present some theorems on approximate fixed-points of roughly contractive mappings and roughly continuous mappings along with illustrating examples.

*Meet & Greet at 16:45, Conference Room / 5th Floor*

Die zunehmende Implementierung neuer Technologien im Straßenverkehr bedeutet nicht nur einen signifikanten Fortschritt in Bezug auf die Prävention von Unfällen und die Erhöhung der Verkehrssicherheit, sondern ermöglicht auch vollkommen neue wissenschaftliche Ansätze und Analysen.

Der interdisziplinäre Workshop „Scientific Computing und Verkehr – die Mobilität der Zukunft", organisiert vom IWR in Zusammenarbeit mit dem Institut für Rechtsmedizin und Verkehrsmedizin Heidelberg, richtet sich an Vertreter verschiedener Fachbereiche und Disziplinen und wird Themen aus den Bereichen „Automatisiertes Fahren“, „Verkehrssicherheit“ und „Verkehrsmedizin“ ansprechen. Hierbei sollen neueste Entwicklungen, laufende Projekte und innovative Forschungsideen vorgestellt werden.

- Automatisiertes Fahren: welche Daten können erhoben und genutzt werden, um den komplexen Strukturen des Verkehrs gerecht zu werden und diese zur Erhöhung der Verkehrssicherheit einzusetzen?

- Verkehrssicherheit: Durch Vernetzung welcher Technologien kann die Verkehrssicherheit erhöht werden? Wie muss die die Infrastruktur der Stadt der Zukunft aussehen und warum?

- Verkehrsmedizin: Wie können innovative computergesteuerte Systeme zur Analyse und Rekonstruktion der Verletzungsmechanik Verunfallter beitragen?

Die Teilnahme am Symposium ist kostenfrei. Da die Anzahl der Teilnehmer jedoch beschränkt sein wird, bitten wir um Registrierung bis spätestens 28.09.2018. Bitte beachten Sie, dass Sie sich für die Tage einzeln anmelden müssen!

Registrierung Tag 1 (11.10.2018)

Registrierung Tag 2 (12.10.2018)

The IWR School 2018 focuses on important modern methods in the field of mathematical optimization. We target young researchers who want to deepen their knowledge of the methods that play a crucial role in solving demanding optimization problems in many application domains in science and engineering, economics, medicine, data analysis and increasingly in industrial and societal problems. The IWR School 2018 covers fundamental concepts, latest innovations and many practical applications of continuous, discrete and mixed-integer optimization as well as optimal control and game theory.

The IWR School 2018 is taught in a series of courses by:

- Tobias Achterberg, Gurobi
- Hans Georg Bock, Heidelberg University
- Christian Kirches, Technical University of Braunschweig
- Ekaterina Kostina, Heidelberg University
- Martine Labbé, Université Libre de Bruxelles and INRIA
- Gerhard Reinelt, Heidelberg University
- Stephen J. Wright, University of Wisconsin-Madison

This is an interdisciplinary workshop in the emerging field of scientific computing that aims to achieve scientific breakthroughs in mathematical modeling and numerical simulations. This one week course will provide an introduction to the most important DUNE modules and especially to DUNE/PDELab. At the end, the participants will have solid knowledge of the simulation workflow from mesh generation and implementation of finite element and finite volume methods for the visualization of results. The topics that will be covered include the solution of stationary and time-dependent problems, local adaptivity, the use of parallel computers and the solution of non-linear PDE_s and systems of PDE_s.

Standard Markov chain Monte Carlo (MCMC) algorithms perform a stationary linear iteration on the space of probability distributions, and hence converge geometrically. Stationary linear solvers were state-of-the-art in the 1950’s, but are now considered very slow precisely because they are geometrically convergent. We show that the same polynomial acceleration methods that have been developed for linear iterative solvers may also be applied to accelerating MCMC, in certain settings.

Prof. Fox is the most recently appointed Romberg Visiting Scholar at the HGS MathComp.

Uncertainty quantification and inverse problems in many variables are pressingly needed tasks, yet high-dimensional functions are notoriously difficult to integrate in order to compute desired quantities of interest. Functional approximations, in particular the low-rank separation of variables into tensor product decompositions, have become popular for reducing the computational cost of high-dimensional integration down to linear scaling in the number of variables. However, tensor approximations may be inefficient for non-smooth functions. Sampling based Monte Carlo methods are more general, but they may exhibit a very slow convergence, overlooking a hidden structure of the function. In this talk we review tensor product approximations for the problem of uncertainty quantification and Bayesian inference. This allows efficient integration of smooth PDE solutions and quantities of interest. Moreover, we can use the low-rank approximation to construct efficient proposal density in the MCMC algorithm for inverse problems. This combined MCMC method is more accurate also if the quantity of interest is not smooth, such as the indicator function of an event.

In this talk we present a recently-introduced multi-layered modeling framework for posing the problem of safe, robust and efficient design and control for rapidly changing electric energy systems. The proposed framework establishes dynamic relations between physical concepts such as stored energy, useful work, and wasted energy, on one hand; and modeling, simulation, and control of interactive modular complex dynamical systems, on the other. In particular, our recently introduced energy state-space modeling approach for electric energy systems is further interpreted using fundamental laws of physics in multi-physical systems, which are modeled as dynamically interacting modules.

This approach is shown to be particularly well-suited for scalable optimization of large-scale complex systems. Instead of having to use simpler models, the proposed multi-layered modeling of system dynamics in energy space offers a promising basic method for modeling and controlling inter-dependencies across multi-physics subsystems for both ensuring feasible and near-optimal operation. It is illustrated how this approach can be used for understanding fundamental physical causes of inefficiencies created either at the component level or resulting from poor matching of their interactions.

This talk is based on the recent paper by M. D. Ilic and R. Jaddivada entitled "Multi-layered interactive energy space modeling for near-optimal electrification of terrestrial, shipboard and aircraft systems”, Annual Reviews in Control, available online May 2018. The paper provides theoretical foundations for Dynamic Monitoring and Decision Systems (DyMonDS) framework envisioned as the next-generation SCADA.

The control design based on joint work with Xia Miao and R. Jaddivada for microgrids and integration of renewable resources and demand response is used as an example to illustrate potential benefits of this approach.

Finally, many open modeling, estimation and optimization challenges/opportunities using this modeling approach are discussed.

*Get-Together at 15:30 Common Room (5th Floor)*

?The transfers of momentum and scalars across the air-sea interface are influenced by small-scale turbulent processes. In spite of extensive existing work on the topic, our understanding of near-surface physics remains incomplete. The measurement of the small-scale dynamics very close to the rapidly moving ocean surface can be challenging! We present laboratory and field measurements of the submillimeter-scale motions in the airflow above waves. A high resolution, large field of view Particle Image Velocimetry (PIV) system was specially developed for the measurements, capable of capturing 2D velocity fields in the turbulent airflow directly above the wavy surface. The system was recently deployed on RP FLIP. Using preliminary field measurements as well as laboratory wave tank measurements, we will discuss the impact of waves on the structure of the wind stress within the wave boundary layer, and in particular how breaking and non-breaking waves influence the momentum flux_s partitioning between viscous, form drag, wave-coherent and turbulent contributions.

We cordially invite all members of the IWR and the HGS MathComp to join us at our 2018 summer party.

As usual, in accordance with university guidelines, we have to charge 10,- EUR per person to cover expenses - children attend free of charge.

July 26, 2016 • 18:00 - 22:00
Mathematikon • Atrium
Im Neuenheimer Feld 205
69120 Heidelberg

! Please make sure to register online for the event !
(Registration Deadline: June 23, 2018)

Online Registration

Further inquiries:
Ria Lynott (ria.lynott@iwr.uni-heidelberg.de)

Quasi-experiments offer opportunities for strong causal inference for evaluation of real-life programs and policies.

I will discuss major approaches and illustrate strengths and limitations with examples.

The task of formally extending the gas flamelet theory to spray flames has been only partially fulfilled and, whereas several spray flamelet models have been derived during the last decades, only few works regarding the spray flamelet equations (SFE) are available in the literature. Therefore, a degree of maturity similar to the one already achieved for gas flames has not yet been reached for spray flames. Among the remaining open issues is the closure of the SFE in mixture fraction space, which includes developing models for the Scalar Dissipation Rate (SDR) and for the different evaporation related sources appearing due to the consideration of a liquid phase.


In this presentation, recent advances in the closure of the SDR are described, which include a reformulation of the spray flamelet equations in terms of the gradient of mixture fraction instead of the SDR itself and the derivation of a transport equation for this new variable. The results are expected to help advancing towards the development of a self-contained spray flamelet theory.

Der Vortrag wird in englischer Sprache gehalten.
For more see the abstract_file:

Menschen machen Modelle interessant! Die immense Vielfalt von menschlichen Attributen, Verhaltensweisen oder Reaktionen sorgt aber auch dafür, dass die Modellbildung ungleich komplexer wird. Um beispielsweise einen Prozess im sozialen oder ökonomischen Leben realitätsnah abzubilden sollte ein möglichst exaktes Bild eines Menschen entworfen werden. Die Abwägung zwischen der Einfachheit eines Modells einerseits und seiner Aussagekraft andererseits stellt dabei eine der größten Herausforderungen dar. Wie gehen Modellierer sicher, dass die gewählten Ansätze nicht nur die jeweilige Forschungsfrage beantworten sondern auch allgemeine Gültigkeit besitzen?

Der Modellierungstag greift die spannende Frage nach der Bildung von „menschlichen Modellen“ auf und fördert den Austausch zwischen Forschern, Entwicklern und Anwendern. Beiträge aus unterschiedlichen Fachrichtungen liefern dazu Denkanstöße und Diskussionsgrundlagen.

! Die Veranstaltung ist öffentlich. Der Eintritt ist frei. Um Anmeldung bis zum 1. Juli 2018 wird gebeten !

The Molecular Sciences Software Institute (MolSSI) is a nexus for science, education, and cooperation serving the worldwide community of computational molecular scientists - a broad field including of biomolecular simulation, quantum chemistry, and materials science. The Institute focuses on the software infrastructure, education, standards, and best-practices that are needed to enable the molecular science community to open new windows on the next generation of scientific Grand Challenges, ranging from the simulation of intrinsically disordered proteins associated with a range of diseases to the design of new catalysts vital to the global chemical industry and climate change. The MolSSI is working to enable the computational molecular sciences community to work together to leverage its diverse capabilities that will reduce or eliminate the gulf that currently delays by years the practical realization of theoretical innovations. Ultimately, the Institute will enable computational scientists to tackle problems that are orders of magnitude larger and more complex than those currently within our grasp. This lecture will provide an overview of the Institute’s activities, goals, and vision.
For more see the abstract_file:

Laser scanning efficiently samples our urban and natural environment. LIDAR systems on tripods, cars, drones, planes and even backpacks are able to collect billions of 3D points in a few hours. What remains challenging is to automatically extract valid geometric information from these points clouds in a similarly efficient way. In the presentation issues with these point clouds will be discussed, followed by some overview of methods to extract geometric information on e.g. trees, traffic signs, tunnels or beaches in a robust and computationally efficient way.
For more see the abstract_file: