CS & Physics Meet-Up by Lamarr & B3D

Session

Overview Talks

OT

29 Nov 2023, 11:10

Joseph-von-Fraunhofer Strasse 25, Floor 3, Room 302 - Lamarr Co-Working Space (Lamarr Institut, TU Dortmund University)

Conveners

Overview Talks: Physics

• There are no conveners in this block

Overview Talks: Machine Learning and Computer Science

• There are no conveners in this block

Overview Talks: Overview Talks

• Jens Buss (Lamarr Institute, TU Dortmund University)

Overview Talks

• There are no conveners in this block

9. Introduction: Radio Astronomy

Dr Ancla Müller (AIRUB)

29/11/2023, 11:10

Physics

Overview Talk

20 mins Talks + 5 mins Q&A

10. Introduction: Exp. Particle Physics

Prof. Johannes Albrecht (Physics Department & Lamarr Institute, TU Dortmund University)

29/11/2023, 11:35

Physics

Overview Talk

20 mins Talks + 5 mins Q&A

5. Introduction: Astroparticle Physics

Dr Dominik Elsaesser, Dr Tim Ruhe (TU Dortmund University)

29/11/2023, 12:00

Physics

Overview Talk

Introductions to Astroparticle physics.

In particular, Gamma-ray Astronomy and Neutrino Astronomy with a glace of Simulation topics.

20 mins Talks + 5 mins Q&A

6. Hybrid Machine Learning for Scientific Discovery

Dr Ramses J. Sanchez (Lamarr Institute, University of Bonn)

29/11/2023, 13:30

Machine Learning and Computer Science

Overview Talk

Hybrid Machine Learning is all about inferring structured representations from empirical data, where by representations I mean transformed views of the data that make it more interpretable, or more usable for modelling and prediction. In this talk I will discuss how one can use neural networks to infer representations that satisfy partial differential equations, which one assumes model the...

12. Introduction to Trustworthy-AI

Dr Maram Akila (Lamarr Institut, Fraunhofer IAIS)

29/11/2023, 13:50

Machine Learning and Computer Science

Overview Talk

This presentation will give a brief overview on the various dimensions comprising Trustworthy AI in general, namely Fairness, Privacy, Autonomy, Transparency and Reliability. A specific focus is given to the last two as they are typically more concerned with the inner workings of the AI system as such. When considering AI as tool for academic, that is scientific, use understanding limitations...

17. Data Bases and Data Storage

Prof. Jens Teubner (DBIS & Lamarr Institut, Fak. Informatik, TU Dortmund)

29/11/2023, 14:10

Machine Learning and Computer Science

Overview Talk

31. Introduction: Human-Centred Systems

Prof. Natalia Andrienko (Lamarr Institute, Fraunhofer IAIS)

29/11/2023, 14:45

Machine Learning and Computer Science

Overview Talk

Human-centered Systems are designed to interact with humans and deliver explainable and comprehensible results.

At the Lamarr Institute, we are developing human-centered approaches for bridging the gap between ML methods and human minds. On the one hand, human-centered systems adapt to human goals, concepts, values, and ways of thinking. On the other hand, these systems take advantage of...

30. Introduction to Embodied AI

Mr Julian Eßer (Lamarr Institute, Fraunhofer IML)

30/11/2023, 09:30

Machine Learning and Computer Science

Overview Talk

Embodied Artificial Intelligence (AI) refers to AI that is embedded in physical systems, such as robots, and can interact with the surroundings. Embodied agents thus learn from experience in order to improve their behavior, comparable to how human learning is based on exploration and interaction with the environment. This talk will give a brief overview of the interdisciplinary field of...

8. Introduction: Resource-aware ML

Dr Sebastian Buschjäger (Lamarr Institute, TU Dortmund University)

30/11/2023, 14:50

Machine Learning and Computer Science

Overview Talk

The scientific area of Resource-Aware Machine Learning tries to "make the most out of a bad situation," i.e., match existing solutions' performance while only using a fraction of the resources or surpassing existing solutions' performance. To do so, we try to bridge the gap between the mathematical concepts of Machine Learning, their expression in software, and their execution in hardware. We...