Summer Term 2023
Training Program Summer term 2023
| Title |
Calculating Free Energy Differences from Molecular |
| 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 |
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| 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
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| 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. |
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 |