Seminars

Summer Term 2023

Training Program Summer term 2023

Title

Calculating Free Energy Differences from Molecular
Simulation: Theory and Practical Applications GS_Academy program_Hansen

Description The free energy difference between
two states of a (bio)molecular system
is one of the central quantities of
interest in (bio)molecular simulation. A
maze of computational techniques to
calculate free energies is nowadays
available that differ in efficiency and
accuracy.
However, most of them are rooted in a
few basic ideas. In this lecture state of
the art methods to calculate free
energy differences in the context of
classical molecular dynamics
simulations will be discussed in light of
these basic ideas. Emphasis is given
to both a theoretical analysis as well
as issues of practical implementation.
The two main types of free energy
calculations, changes in the
Hamiltonian (so-called alchemical
perturbations) and changes in the
configuration will be covered. Finally,
the participants will present and
discuss their own free-energy related
research questions.
Lecturer Niels Hansen
Language English
Time tba
SWS 2
ECTS 3
Registration Please register via email niels.hansen@itt.uni-stuttgart.de
Title Mathematics of Shock Waves GS_Seminar_Rohde
Description
  • Euler's equations
  • Prospective talks correspond to a section in either the (stone-old) book
    R.J. LeVeque, Numerical methods for conservation laws. Birkhäuser 1992
    and the (almost brand-new) book
    R.J. LeVeque et al., Riemann problems and Jupyter solutions. SIAM 2020.
  • Possible lectures and applications:
    • Linear advection
      . Acoustics
      . Burgers’ equation
      . Traffic flow: vehicules and pedestrians
      . Underground transport of fluids: Buckley-Leverett equations
      . Shallow water equations
      . Shallow water equations and tracers
      . Gas dynamics
Lecturer Christian Rohde
Language English
Time tba
SWS tba
ECTS tba
Registration Please register via email christian.rohde@mathematik.uni-stuttgart.de
Title Fundamentals of turbulent flows: Physics and Data Analysis GS_Academy Course_Chu
Description Having completed this course, students will be
able to:
Statistical description of turbulence including
the probability theory, correlations, spectra,
turbulent kinetic energy transport and others.
Isotropic turbulence: Kolmogorov hypothesis,
spectra ranges: energy-containing, inertial,
dissipation
Wall-bounded turbulence: law of the wall,
Townsend´s wall-attached eddy model,
coherent structures, effect of wall roughness
Data-driven data analysis methods, POD, DMD,
Autoencoder
Direct numerical simulation (DNS): history
resolution requirement,
Large-eddy-simulation (LES): explicit, implicit
models, wall-resolved/wall-modeled LES
Hands-on programming and practice with POD,
DMD data-driven analysis (Matlab), LES
simulations with OpenFOAM
Student seminar with publication presentation:
one group with 2 students, presentation of
notable journal papers from a given pool, take
Q&A from the audience and docents.
Lecturer Xu Chu and Heng Xiao
Language English
Date to be discussed
Time to be discussed
SWS 4
ECTS 6
Proof of Attendance Regular presence, presentation and interview
Registration Please register via email Campus [Module number: 107350]
Title Modeling of Turbulent Flows: Physical and Data-Driven Methods GS_Academy Course_Xiao
Description Having completed this course, students will be able to:
Derive the exact equations governing turbulent flows
Understand different modeling approaches (RSTM,
LEVM, RANS)
Implement 1- and 2-equation RANS models in a CFD
code (programming)
Perform RANS simulations with OpenFOAM
Understand the limitations of linear eddy viscosity
models and the sources of modeling error
Understand how to analyze data from a turbulent-flow
simulation (RANS)
Familiar with the recent developments in data-driven
turbulence modeling
Understand the strengths and weakness of various
approaches in data-driving modeling (neural networks,
symbolic regression, decision-tree models)
Specific course contents include:
Introduction to turbulence flows and their modeling
approaches
Derivation of RANS equations and the closure
problem
Algebraic models
One- and two-equation models
Reynolds stress transport models
Origin of uncertainties in turbulence models and
methods to quantify them
Neural networks for learning models
Learning models from sparse data
Lecturer Heng Xiao and Xu Chu
Language English
Date to be discussed
Time to be discussed
SWS 4
ECTS 6
Proof of Attendance Regular presence, presentation and interview
Registration Please register via email Campus [Module number: 107360]

Winter Term 2022/2023

Title Research Software Engineering 102
Description We build up on RSE fundamentals (Unix shell, Git, Python) as learned, for example, during a Software Carpentry workshop and study methods and tools used to ensure good software engineering:

- Git workflows
- Containerization
- Testing and continuous integration
- Building and packaging
- Software design principles

Skills in these topics are crucial for developing or contributing to quality-assured software in collaborative environments and are very useful in today's research landscape.
Lecturer Benjamin Uekermann | Bernd Flemisch | Dennis Gläser
Language English
Time 9 am to 6 pm
SWS 2
ECTS 2
Registration Please register via Campus. If you do not have a student account (yet), please write a amil to benjamin.uekermann@ipvs.uni-stuttgart.de

 

Title Deep Learning for the Sciences
Description

Deep learning has been successfully applied in a wide range of use cases and specifically in applications involving visual and textual data. Modern machine translation systems and search engines, for example, are using language models trained on large text corpora. Increasingly, deep learning is also applied to problems arising in the sciences and engineering. For instance, deep learning for graphs is used to learn simulators from data. The figure on the right shows a particle simulation obtained from a graph neural network trained on simulation traces from a numerical solver. The advantage of using deep learning in this context is its ability to integrate the simulation into a larger neural network with a corresponding loss function and train the resulting model end-to-end.

Other applications of deep learning can be found in chemistry, the biomedical sciences, and engineering disciplines, where use cases range from drug-protein interaction prediction to modeling fluid dynamics. Since machine learning and specifically deep learning will be increasingly used in disciplines of science and engineering, this seminar’s goal is to provide an overview of applications, to give students a deeper understanding of recent work, and to have an opportunity to learn reading, analyzing, and engaging with scientific papers. If possible, the students are also encouraged to demo the application to the seminar.
Target Group

GS SimTech-Members, Participants of the seminar are expected to have completed the course “Machine Learning", "Reinforcement Learning", or a related course.

Lecturer Mathias Niepert
Language English
Registration Please register via Campus. The seminar's number is 021895000.
Title Digital Literacy in Research and Teaching
Description There exist a lot of tools to make our work in research, teaching, and co-working in groups with other students or researchers easier and more effective, for example how to find bugs in our code faster using debugging tools, how to keep track of our change history with a version control system, or how to visualize our results in a convincing way. Especially in times of the Corona pandemic, when most people including students and researchers worked from home, it became clear that teaching knowledge and skills to work with these tools is a significant part of a scientific environment. Previously, these skills were often shown to students in personal meetings in the scope of a student thesis. In this lecture, various principles and tools are introduced, which are helpful in the context of scientific work in general and scientific programming in particular.
Lecturer Prof. Dr.-Ing. Jörg Fehr, Arnim Kargl, Sibylle Hermannr
Style Lectures are held biweekly. Every other week, in Inverted Classroom style, students present their solutions to the homework exercises, and the comments/additions of the students to the course content are discussed.
Documents All material can be found on ILIAS and bwSync&Share
Language English
Time 11:30 am to 1:00 pm
SWS 2
ECTS 3
Exam/Proof of Attendance

Depending on the number of participants, the exam will be in written or oral form.

Students who do not take the exam but need a proof of attendance (e.g. PhD students, FÜSQ participants) have to present their results for at least one minor and one major exercise in the Inverted Classroom meetings.

Registration For participation please register for the lecture in C@MPUS. This will give you access to the ILIAS group and the shared working space on bwSync&Share

Summer Term 2022

Title Novel methods in simulation science
Description  
Lecturer Paul Bürkner, Kristyna Pluhackova, Benjamin Unger
Language English
Date  
Time Thursdays, 3:45 pm to 5:15 pm
Place 7.04
SWS  
ECTS  
Proof of Attendance  
Registration tba

Winter Term 2021/2022

Title Science Communication
Description

How do I get to the heart of my topic and how do I communicate it to the public? This workshop series offers a DeepDive into the most important techniques of science communication: we look for and find the topic in our subject, we find best sentences, write a pitch, practice repartee for interview situations and learn how a gripping speech is structured. In the end, everyone will have something in hand: a self-written press release, a speech concept, a poster presentation or an artistic format. And we will have a lot of fun.

Lecturer Eva Wolfangel (https://ewo.name/)
Language depends on participants, German and English is possible
Date 28 October
4 November
18 November
2 December
Time 9 am to 1 pm
Place tba
SWS 2
ECTS 3
Proof of Attendance  
Registration Please register via pamela-alina.conde-morales@simtech.uni-stuttgart.de
Title Advanced Topics in Simulation Science
Description In the seminar we discuss advanced topics in simulation science centering around Bayesian statistics, molecular dynamics simulations, and surrogate modeling via model order reduction and machine learning. After introductory talks on these topics by the seminar organizers, the participants will present recent research results on these topics.
Lecturer Paul-Christian Bürkner, Kristyna Pluhackova, Benjamin Unger
Language English
Date Thursdays
Time 2 - 3:30 pm
Place Hybrid event, room: tba
Participants Master students, PhD students
SWS 2
ECTS 3
Proof of Attendance  
Registration For participation please register for the lecture in C@MPUS. This will give you access to the ILIAS group.
Title Digital Literacy in Research and Teaching
Description There exist a lot of tools to make our work in research, teaching, and co-working in groups with other students or researchers easier and more effective, for example how to find bugs in our code faster using debugging tools, how to keep track of our change history with a version control system, or how to visualize our results in a convincing way. Especially in times of the Corona pandemic, when most people including students and researchers worked from home, it became clear that teaching knowledge and skills to work with these tools is a significant part of a scientific environment. Previously, these skills were often shown to students in personal meetings in the scope of a student thesis. In this lecture, various principles and tools are introduced, which are helpful in the context of scientific work in general and scientific programming in particular.
Lecturer Prof. Dr.-Ing. Jörg Fehr, Georg Schneider, Sibylle Hermann
Language English
Date Lecture takes place on Monday starting on Monday, October 25.
Time 11:30 am to 1:00 pm
Place V9.01
SWS 2
ECTS 3
Proof of Attendance

Depending on the number of participants, the exam will be in written or oral form.

Students who do not take the exam but need a proof of attendance (e.g. PhD students, FÜSQ participants) have to present their results for at least one minor and one major exercise in the Inverted Classroom meetings.

Registration For participation please register for the lecture in C@MPUS. This will give you access to the ILIAS group and the shared working space on bwSync&Share

Summer term 2021

Title Recent scientific advances in robotics (online)
Description This novel online course addresses both Master and PhD students (both SimTech and IMPRSIS) with basic knowledge and experience in robotics, mechanics, engineering, controls, materials, and computer science. High-impact robotics science-related journal articles published recently in top scientific journals, such as Science, Nature, Science Robotics, PNAS, Nature Materials, and Science Advances, will be selected and assigned to the students. The students will present and discuss these papers with guidance and comments from the professor. 
Lecturer Prof. Metin Sitti, IMPRS-IS
Language English
Date Thursday June 10th, 1:30-3 pm via Zoom; July 14th and 15th, 2021, time tbd.
Proof of Attendance Presenting a paper and active participation in discussions
Registration You may then register with the following link: https://ilias3.uni-stuttgart.de/goto.php?target=grp_2480134_rcodeV3GQgnjsdY&client_id=Uni_Stuttgart

Please direct any questions to Prof. Metin Sitti (sitti@is.mpg.de).

Title Mathematical Theory for Simulation Practitioners (online)
Description

This novel course addresses master and PhD students with basic knowledge and experience in continuum mechanics based mathematical modeling and numerical simulations of natural or technical processes. Its goal is to provide or refresh or widen the necessary background information from mathematics, both concerning model formulation and validity and discretization and solution methods. Due to this wide span, the lecture can only touch selected topics, also relying on the active reading activity of the participants. In particular, specific interests and questions of the participants can be addressed in the discussion hours. Examples of questions which may come up and be discussed are

  • Is my model thermodynamically consistent ?
  • What means mathematically rigorous or formal, what are the consequences ?
  • What am I allowed to do with which functions ?
  • What is a good discretization method ?
  • Is my discretization locally mass conservative, if not, what to do?
  • Etc.
Lecturer Prof. Peter Knabner
Language English
Date will be announced soon
Time will be announced soon
SWS  
ECTS  
Proof of Attendance Lectures : 2 semester hours/week
Reading discussion: 1 semester hour/week
Registration The course will be webex- based, the exact dates will be announced soon. For better planning, you may send my an email  (knabner@math.fau.de), indicate your interest and also if necessary indicate which dates are impossible for you.

More information

Winter term 2020/2021

Title Digital Literacy in Research and Teaching (online)
Description There exist a lot of tools to make our work in research, teaching, and co-working in groups with other students or researchers easier and more effective, for example how to find bugs in our code faster using debugging tools, how to keep track of our change history with a version control system, or how to visualize our results in a convincing way. Especially in times of the Corona pandemic, when most people including students and researchers worked from home, it became clear that teaching knowledge and skills to work with these tools is a significant part of a scientific environment. Previously, these skills were often shown to students in personal meetings in the scope of a student thesis. In this lecture, various principles and tools are introduced, which are helpful in the context of scientific work in general and scientific programming in particular.
Lecturer apl.-Prof. Dr.-Ing. Jörg Fehr, Georg Schneider, Sibylle Hermann
Language English
Date Lecture takes place on Monday starting on Monday, November 2, 2020
Time 11:30 am to 1:00 pm
SWS 2
ECTS 3
Proof of Attendance Depending on the number of participants, the exam will be in written or oral form.
Registration For participation please register for the lecture in C@MPUS. This will give you access to the ILIAS group, where all course material is provided.

Summer term 2020

Title Human uprigth stance: Designing bio-inspired controllers to stimulate a multiple-muscle system (online)
Lecturer Prof. Syn Schmitt
Language English
Date 18 and 19 June 2020
Time 9:30 am to 6:30 pm
SWS 2
ECTS 3
Proof of Attendance Tutorial Talks/Presentation
Registration Please indicate your interest in an active participation by sending an email to syn.schmitt@simtech.uni-stuttgart.de.
Title Programming Skills for Simulation Software (online)
Lecturer Bernd Flemisch, Ralf Diesterkämper, Sybille Hermann
Language English
Topic Refining and evaluating simulation models frequently requires implementing simulation software. To accelerate the implementation process, this seminar aims at improving your programming skills. If you already have basic coding experience in Python, Java, Scala or C/C++, you can refine your programming skills in hands-on implementation tasks on popular data-structures and algorithms in computer science. In weekly online sessions, you are given 1 to 3 programming tasks that you should solve in a sandbox environment and discuss with the group. The amount and difficulty of the tasks is dynamically adapted based on the participants’ skills and feedback.
Time Start:
Tuesday 15:45-17:15 CEST
Starting May 26th via WebEx
SWS 2
ECTS 3
Proof of Attendance Regular online presence and active participation in discussions
Registration If you like to participate, please contact rdm@simtech.uni-stuttgart.de. The seminar is limited to 10 participants.

Winter term 2019/2020

Title The Mathematics of Gaussian Processes in Control
Lecturers Prof. Carsten Scherer
Dr. Sebastian Trimpe

Summer term 2019

Title From data to model: how to build up a biomechanical mathematical model starting from recorded data of muscular activity
Lecturer Simona Galliani, Harnoor Saini, Johannes Walter
Title Stochastic and Statistical Topics in Modeling and Simulation: Artifical Neural Networks from a statistical point of view
Lecturer Prof. Dr.-Ing. Wolfgang Nowak

Winter term 2018/2019

Title Continuum Mechanics of Multiphase Materials
Lecturer Dr.-Ing. Arndt Wagner
Title Homogenization as upsacling technique
Lecturer Dr. Carina Bringedal

Summer term 2018

Title Machine learning methods for molecular simulations
Lecturer Prof. Jürgen Pleiss, apl. Prof. Niels Hansen
Title Stochastic and Statistical Topics in Modeling and Simulation - Algorithms for Data Assimilation and Conditional Samplin
Lecturer Prof. Wolfgang Nowak
Title Reducation Methods
Lecturer Prof. G. Schneider, Prof. B. Haasdonk, Dr. Ashish Bhatt

Winter term 2017/2018

Title Selected topics on multifield problems in image analysis and visualization
Lecturer Dr. Steffen Frey, Dr. Andreas Alnger
Title Entwicklung von Simulationen und wissenschaftlicher Software
Lecturer JP Andreas Pott
Title Stoachstic and Statistical Topics in Modeling and Simulation - Part 3: Theories for Knowledge and Uncertainty
Lecturer Prof. Wolfgang Nowak

Summer term 2017

Title Entwicklung von Simulationen und wissenschaftlicher Software
Lecturer JP Andreas Pott
Title "Stochastic and Statistical Topics in Modelling and Simulation" Part 3: Stoachstic Approaches for Data-Integrated Simulation
Lecturer Prof. Wolfgang Nowak
Title Modelling and Optimization of Hard Problems (BYOP)
Lecturer Dr. Colin Glass
Title User Centred Research Methods
Lecturer Prof. Albrecht Schmidt, JP Niels Henze

Graduate Academy

 
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