Teaching by the Chair for Network Dynamics

Beyond standard courses in undergraduate Physics, the Chair for Network Dynamics offers courses covering advanced topics of Statistical Physics and Nonlinear Dynamics and Complex Systems Modelling. These courses cover the foundations of network theory, dynamical systems and network dynamics with examples from various applications ranging from the description of flows in traffic networks or power grids to information processing in neural networks. More in-depth courses on individual topics cover, for example, the application of network dynamics and game theory to modelling the dynamics of sustainable human mobility. These courses are usually offered as Specialization Lectures for M.Sc. Physics students but are also suitable for motivated third-year B.Sc. Physics (or equivalent fields) students with a background in Statistical Physics and Computational Physics.

 

Team Seminar: Frontiers in Nonlinear and Network Dynamics

Tuesdays, 13:00-14:30 (4. DS) online

Responsible tutors: Marc Timme | Malte Schröder | Xiaozhu Zhang

What are current challenges in the field of Nonlinear Dynamics, Network Dynamics and beyond? Can we observe and perhaps co-define new developing trends? Let us discuss up to date ideas, even partial results and broad perspectives on which are relevant systems, how to analyze and model them, how to develop analysis tools and algorithms and which are collective phenomena in these systems.


Summer term 2021

Seminar: Statistical Physics and Dynamics of Bioinspired Computing (Hauptseminar)

Wednesdays, 11:10-12:40 (3. DS)

Lecturers: Marc Timme | Fabio Schittler-Neves

Statistical Physics and Nonlinear Dynamics have substantially contributed to understanding the basics of artificial neural network modeling and analysis. In this seminar, we will learn the basics of such approaches. Contents include some foundations of computation and historical remarks, basics of information theory, binary state neurons and simple and multi-layered perceptrons, the Hopfield model of associative memory, reservoir computing, heteroclinic computing, basic notions of machine learning, signal compression, and a number of example applications as they are currently employed in industry and elsewhere. The course is not suitable as a replacement for a machine learning or neural networks course given in Computer Science, it rather complements it by emphasizing the perspective of Dynamical Systems' Theory and highlighting alternative ways of processing information.

Sign up in OPAL

 

Lecture: Network Dynamics and Research on Complex Systems (Vertiefungsvorlesung)

Wednesdays, 14:50-16:20 (5. DS); Thursdays, 11:10-12:40 (3. DS)

Lecturers: Marc Timme | Malte Schröder

The dynamics of networks dominates our lives, from molecular reactions in our cells to neural circuits in the brain and from traffic networks to electric power grids. You will learn what network dynamical systems are, how to model them, how collective dynamical phenomena emerge and how to understand some of them. You will also learn to present your insights to a broad, interdisciplinary audience.

Sign up in OPAL

 

Ringvorlesung Mobility4Future - A path towards climate-compliant mobility

Wednesdays, 16:40-18:10 (6. DS) online

Organizers: Marc Timme | Regine Gerike

How do we as a society establish an ecological and economical sustainable, climate-friendly mobility? In a diverse series of lectures with TUD-internal and external experts, we will shed light on various aspects of the current and future development of transport systems and evaluate novel options for human mobility.

Schedule and sign-up here.

Recordings of previous lectures are available here.


Summer term 2018

Seminar on Network Dynamics (Hauptseminar)

Wednesdays, 11:10-12:40 (3. DS) @ Zellescher Weg 17 *BZW room A120

Lecturers: Marc Timme | Malte Schröder

The dynamics of networks dominates our lives, from molecular reactions in our cells to neural circuits in the brain and from traffic networks to electric power grids. You will learn what network dynamical systems are, how to model them, how collective dynamical phenomena emerge and how to understand some of them. You will also learn to present your insights to a broad, interdisciplinary audience.

 

Tutorial: Dynamics of Complex Systems and Networks

Tuesdays, 11:10-12:40 (3. DS) @ Zellescher Weg 17 *BZW room A120

Tutors: Marc Timme | Malte Schröder | Xiaozhu Zhang

We offer a tutorial accompanying the Seminar on Network Dynamics as well as research topics on general complex systems' dynamics. Here complex systems are broadly defined as systems exhibiting several interacting units that collectively exhibit phenomena not explainable from individual unit properties alone.

You will learn how to systematically model and analyze collective (dynamical) phenomena in complex systems and networks, how to create own results, both by mathematical analysis and computer simulation and, most importantly, strategic modeling. You will also learn how to present own or others' work in front of a cross-disciplinary 'complex systems' audience or readership

 

Team Seminar: Frontiers in Nonlinear and Network Dynamics

Tuesdays, 13:00-14:30 (4. DS) @ Zellescher Weg 17 *BZW room A120

Responsible tutors: Marc Timme | Malte Schröder | Xiaozhu Zhang

What are current challenges in the field of Nonlinear Dynamics, Network Dynamics and beyond? Can we observe and perhaps co-define new developing trends? Let us discuss up to date ideas, even partial results and broad perspectives on which are relevant systems, how to analyze and model them, how to develop analysis tools and algorithms and which are collective phenomena in these systems.

 

Ringvorlesung - General Natural Science Lecture, 3 May 2018

Collective Network Dynamics & Future Power Grids

Speaker: Marc Timme

Time: Thursday, 3 May 2018, 16:40-18:10 (6. DS)
Location: ASB, HS 28

(lecture in German)