HGS MathComp Curriculum & Events

R is a freely available software environment for statistical computing and graphics. This course is a systematic introduction to R. The course covers: the basic R language, data management, descriptive statistics, statistical testing and exploratory data analysis and advance graphical and analytical techniques.

Who should attend?
Data analysis and students with basic knowledge in statistics will benefit from this course. The course is intended as a first course in R but not as a first course in statistics.

How you will benefit?
You will learn to use R for simple statistical analysis and graphics. All practical exercises with solutions are included with the course material.

Course content
Day 1: Introduction to R
• Introductory concepts of R
• Data structures, objects and classes
• Data management with R (indexing and other advanced techniques)
• Descriptive statistics with R
• Classical graphical functions (scatter plots, conditional plots, histograms, etc)

Day 2: Data visualization and data analysis with R

• Lattice plots and advance graphical functions in R
• Further on graphical functionality (ggplot2)
• Introduction to statistical analysis with R
• Statistical inference and computer simulation
• Exploratory multivariate analysis


Day 3: Statistical Modeling with R
• Linear regression models: model building, variables selection, model checking, resistant regression models
• Modeling binomial data: Logistic regression and its extensions
• Modeling count data: log-linear models for contingency tables and multinomial modeling
• Introduction to survival regression with R

For registration and

The aim of this compact course is an introduction to modelling of biological and biochemical processes using ordinary (ode) and partial differential equations (pde). We will learn what kind of processes can be modelled by differential equations and which assumptions are necessary. Moreover, we will learn methods for the analysis of such models and apply them to some important examples. Abstract results like existence theorems will be stated, but we will not prove them.

Target Group:
Students of any level with interest in modelling. We assume a basic knowledge of analysis and linear algebra. Knowledge about odes might be useful, but is not necessary.

Program:
1 Introduction
2 Modelling using odes
• The law of mass action
• Michaelis-Menten kinetics
• Examples: The logistic equation, Lotka-Volterra equations
• Steady states and linearization of nonlinear models
3 Modelling using pdes
• Reaction-diffusion equations
• Pattern formation with the Turing mechanism
• Reaction-diffusion-ode-models
• Structured population models

Please register here:

PREREQUISITES:
suitable for diploma/master students in physics, mathematics, and computer science

SCHEDULE:
Monday, February 23:
10:15 - 11:45, 13:15 - 14:45, 15:00 - 16:30
Tuesday, February 24:
10:15 - 11:45, 13:15 - 14:45, 15:00 - 16:30
Wednesday, February 25:
10:15 - 11:45, 12:00 - 13:30

LITERATURE:
Bernd Jähne, Digitale Bildverarbeitung und Bildgewinnung, 7. Aufl., Springer-Verlag 2012
(further literature will be given during the course)

CONTENTS:
The topics of the lecture includes all the basic knowledge about image sensors everybody should know who is applying image processing techniques. In particular:

Radiation detection:
Basic principle of quantum detectors, quantum efficiency and responsivity, dark signal, overall system gain, spectral sensitivity;
non-silicon solid-state imaging: InGaAs, HgCdTe, InSb, QWIP, superlattice detectors;
indirect (thermal) detectors: pyroelectricity, microbolometers

Imaging detectors:
The charge-coupled device (CCD), CCD sensor architecture, frame transfer, interline transfer, electronic shutter, microlens arrays;
CMOS imaging sensors and active pixels, scientific CMOS sensors, color and spectral sensors, high-speed imaging, artefacts of image sensors

Standard interfaces for digital cameras:
Camera Link, Camera Link HS, CoaxPress (CXP), Firewire (IEEE1394), USB2, USB3 Vision, GigE Vision, towards a standardized interface: GenICam

Performance characterization for image sensors
EMVA 1288 standard, noise model for a linear camera, photon transfer method, signal to noise ratio (SNR), signal saturation, absolute sensitivity threshold, dynamic range (DR)
Dark current and auto-saturation time
Spatial nonuniformities and defective pixel: spatial variances, spectrogram method, logarithmic histograms, profiles

Practical issues:
Measuring equipment for camera performance characterization,
Application-oriented camera selection according to different criteria

tba.

tba.

tba.

tba.

tba.

tba.

tba.

tba.

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:

Hintergrund:
Bewerben und Auftreten im Assessmentcenter (AC) ist wie Flirten: Wer zu langweilig und 08/15 ist oder den falschen Ton trifft, wird abgewiesen. Zwei Vorgehensweisen können nun angewandt werden: die quantitative oder die qualitative Strategie. Die quantitative Strategie bedeutet z.B. mehr schlechte Bewerbungen schreiben. Sprich: einfach mehr flirten in der Hoffnung, dass auch ein blindes Huhn...usw. Die qualitative Strategie verspricht, durch intelligente Bewerbungen und kluges Auftreten im AC mehr Erfolg zu haben. Das bedeutet beim Bewerben wie beim Flirten: mehr Auswahl.
Ziel dieses Workshops ist es, den Teilnehmern neben Vorbereitungsstrategien ein sicheres und überzeugendes Auftreten sowohl im Vorstellungsgespräch als auch im AC beizubringen.

Inhalt:
Die Teilnehmer durchlaufen reale Übungen wie Selbstpräsentation, Rollenspiel, Vorstellungsgespräch, Stressinterview.
Sie lernen sicherer und souveräner aufzutreten.
Die Teilnehmer erfahren Techniken, einen Vortrag packender zu gestalten.
Durch Übungen wird die Schlagfertigkeit im Gespräch und vor der Gruppe erhöht.
Mehr Gehalt zum Einstieg verhandeln

Nach dem Seminar werden die Teilnehmer:
Souverän und sicher vor der Gruppe präsentieren.
Körpersprache und Gesagtes besser verbinden können.
Mit ihren neuen Kompetenzen aus der Masse hervorstechen.
Ein präziseres Sprachbild haben.
Sich auf das nächste Assessmentcenter oder Vorstellungsgespräch freuen!

Bitte hier anmelden:
http://hgs.iwr.uni-heidelberg.de/Portfolio_HGS/VERANSTALTUNGEN/reg_form/reg_form.php?id=113

Effective Grant Writing for Scientists
Goals:
- Obtaining a thorough understanding of how successful grant applications are written
- Learning to write readable texts in English
- Understanding the reviewing process for grant applications
- Gaining practical experience in writing and evaluating grant applications
- Obtaining an overview over funding agencies and funding opportunities
The aim of this course is to familiarize participants with the strategies for writing successful grant / fellowship applications to various funding bodies. It consists of lecture-style sequences with active participation by the audience dealing with the theory of good scientific writing, the basics of grant applications and the principles of different funding bodies, as well as hands-on exercises on aim definition, structuring a workplan and writing a grant summary. Additional information and exercises on writing good scientific texts in English will deepen the writing experience
Participants will be asked to prepare a short “mini-grant application” (3 pages + Scientific CV) in preparation to the course, which will be due approx. 5 days before the start of the course – please take this into consideration when planning participation in this course. These applications will be evaluated by other participants individually before the course and in an evaluation session within the course and each participant will also evaluate 3-4 proposals by others in the 4-5 days before course start. This will provide extensive feedback for all participants on their applications, but most importantly, will provide a clear impression of the situation and the view of potential evaluators.

The lecture will be given in English.
Practical Part: Thu 12:00-14:00, start: Oct.23, 2014
Location: INF 350/OMZ, R.U013

More information:
https://elearning2.uni-heidelberg.de/course/view.php?id=6513

This winter school will foster advanced knowledge for the participating graduate students in several areas related to simulation and optimization of extreme fluids. Within this broad field the winter school will concentrate on the key issues

* Shape Optimization (Lecturer: Volker Schulz)
* Fluid Structure Interaction (Lecturer: Thomas Wick)

Within these key issues, the following topics will be treated:

Shape Optimization:

* Fundamentals of shape calculus
* Second shape derivative and Riemannian shape-SQP
* Academic and industrial applications

Fluid Structure Interaction:

Physical and Computational Modeling:
Governing physical equations of fluids and solids; constitutive laws; Eulerian, Langrangian, and arbitrary Langrangian-Eulerian (ALE) reference frames, ALE mesh motion techniques and their impact; monolithic and variational coupling of fluids and solids; brief excursion to other coupling techniques such as fully Eulerian.

Discretization:
Implicit schemes for temporal discretization based in finite differences and fractional-step-theta schemes; spatial discretization with Galerkin finite elements; inf-sup stable finite elements for Navier-Stokes; solution of nonlinear systems with Newton_s method.

Cost-Efficient Solution Strategies, Optimization, and Applications:
Mesh adaptivity; a variational dual-weighted residual method for goal-oriented mesh adaptivity; adjoint-based optimization for fluid-structure interaction; applications towards benchmarks problems, flapping settings and solid growth.

The winter school is supported by the “Mathematics Center Heidelberg” (MATCH) within the special semester on Fluid Structure Interaction. Furthermore, the “Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences” (HGS) and the International Research Training Group 1754 “Optimization and Numerical Analysis for Partial Differential Equations with Nonsmooth Structures” (Munich - Graz) support the workshop as well as an autumn school for doctoral candidates which takes place immediately after the workshop at the “Interdisciplinary Center for Scientific Computing” (IWR).

The optimal control of human walking movements requires simulation techniques, which handle the contact_s establishing and releasing between the foot and the ground. The system_s dynamics switches non-smoothly between phases with and without contact making the system hybrid.

During motion phases without switch, the direct transcription method Discrete Mechanics and Optimal Control (DMOCC) is used to transform the optimal control problem into a constrained optimisation problem. It involves a mechanical integrator based on a discrete constrained version of the Lagrange-d_Alembert principle. This integrator represents exactly the behaviour of the analytical solution concerning the consistency of momentum maps and symplecticity. To guarantee the structure preservation and the geometrical correctness during the establishing and releasing of contacts, the non-smooth problem is solved including the computation of the contact or contact release configuration as well as the contact time and force, instead of relying on a smooth approximation of the contact problem via a penalty potential.

While in a first approach, the sequence (not the switching time) in which the closing and opening of contacts follow each other is considered as known, a more general approach is the optimisation of the whole locomotion requiring a combined model including transitions between the different dynamical systems. Integer valued functions can be used to control if and when the switch to another dynamical system occurs, i.e. they permit to control the sequence and switching times of the dynamical systems. A variable time transformation allows to eliminate the integer valued functions and therefore to apply gradient based optimisation methods to approximate the mixed integer optimal control problem.

tba.

Bei der letzten Jahrestagung der deutschen Fachvereinigung für die Digital Humanities bot die Eröffnungskeynote unter dem Titel „Informatik als Geisteswissenschaft“ eine Interpretation des Verhältnisses der Disziplinen an, die auf Grund methodischer Eigenschaften der Disziplinen aufzeigte, dass die Informatik den Naturwissenschaften – als Objektwissenschaften – nicht wirklich zuzurechnen sei. Während es einen klaren methodischen Unterschied zwischen den Natur- und den Geisteswissenschaften gäbe, gäbe es keinen wirklichen Grund, warum kein Nahverhältnis zwischen der Informatik und den Geisteswissenschaften möglich sein solle.

In der Tat scheinen mir epistemologisch die beiden Disziplinen weniger fremd, als man meinen sollte. Dazu die folgenden Thesen:

(1) Seit ca. 1960 gibt es einen Problembereich, in dem Vertreter beider Disziplinen versuchen, die methodischen Möglichkeiten der Anwendung der Techniken der Informatik auszuloten. Die Fortschritte sind langsam aber stetig.

(2) Diese Entwicklung wird von heftigen Ausschlägen einer Wellenbewegung überlagert, die von Konjunkturen und Krisen der Anwendung informationstechnischer Werkzeuge auf geisteswissenschaftlich relevante Materialgruppen geprägt ist. Die jüngste dieser Konjunkturen heißt „Digital Humanities“.

(3) Unabhängig von derartigen Konjunkturen gibt es Problemklassen, bei denen die Anwendung bekannter Techniken auf geisteswissenschaftliche Materialien die Grundlagen geisteswissenschaftlicher Arbeit handwerklich so gründlich umgestalten kann, dass sich für die Geisteswissenschaften methodische Konsequenzen ergeben, gleichzeitig aber Defizite der angewandten Techniken erkennbar werden.

(4) Diese Defizite rühren daher, dass die „Information“ auf denen die Geisteswissenschaften ihre Analysen gründen, eine Reihe von Eigenschaften hat – genuine Inkonsistenz und Unschärfe – die nur durch eine Verallgemeinerung von Annahmen der Informatik über die Grundlagen der Repräsentation von Information gelöst werden können.

The workshop is concerned with the theory and the numerics of bilevel optimal control problems, which are optimal control problems, mainly in ordinary differential equations, with two levels of optimization. We intend to discuss theoretical aspects like optimality conditions and stationarity concepts of this problem class, but we are also concerned with the development of efficient solution algorithms and the corresponding convergence theory. Furthermore, challenging applications from fields like image processing, medicine or robotics are presented.

Targeted Audience: MS & PhD students in the beginning semesters of their research (Dissertation/thesis)

Workshop Objectives:
- To introduce to the participants the objectives of MS/PhD research in order to enable them in targeting these objectives more cautiously and from the outset of their study programme.
- To share the various processes and timeframes which are crucial to understand for a smooth beginning and completion. For example the process and time frames for degree programme, research project, research write-up.
- The workshop also aims at sharing useful tips in pushing through different stages and challenges and in pointing out certain pitfalls that every researcher must avoid. Moreover, it will draw attention towards some essential skills needed by a researcher at this level.

Workshop Nature & Plan:
- A multimedia / presentation based interactive workshop interspersed with classroom questioning and discussion.
- One hour and thirty minutes will be dedicated to Resource Person led inputs in the session.
- Final thirty minutes will be devoted to questions from the audience.

Please register here:
http://hgs.iwr.uni-heidelberg.de/Portfolio_HGS/VERANSTALTUNGEN/reg_form/reg_form.php?id=107

The aim of this workshop is to bring together computer scientists and mathematicians to provide an overview of the state-of-the-art in numerical methods for the solution of partial differential equations and related fields in order to discuss the mutual implications of expected exascale hardware and these numerical algorithms. The workshop is part of DFG_s Priority Programme 1648 "Software for Exascale Computing". The conference will be take place at the Interdisciplinary Center for Scientific Computing (IWR).

The workshop targets female junior researchers, PhD students and students of Mathematics with a focus on optimization. The goal of the workshop is to provide advanced scientific training in the field of optimization as well as an opportunity for networking in the optimization community. By lectures of invited speakers working in all areas of optimization in academia and industry we want to present on the one hand a wide scientific spectrum of topics in mathematical optimization as well as different possible career models in this field. In addition to these lectures there will be ample opportunities for discussions and an exchange of experiences. All participants are invited to actively participate in poster presentations.