Center for Artificial Intelligence and Data Science

AI Talks @JMU Winter 2023/24

In the 5th series of AI talks, selected guests and new CAIDAS members present their research with exciting talks on current activities and projects. The talks will take place on tuesdays at 16:15. The talks will be 45 minutes, followed by a 15-minute discussion. The language of presentation is English.

Afterwards there will be the opportunity for a casual get together. At the first and the last talk of the series there will also be some drinks and snacks.

If no other information is given, the talks will take place in Z6 building in room 0.002.

See below for details.

past talks:

past series:

past talks

21 November

Junior Professorship of Applied Microeconomics, esp. Human-Machine Interaction, JMU Würzburg

Topic: Can Less Be More? User-Driven Data Selection and Targeting in AI Recommender Systems

24 November

Dr. Florian Mai

Language Intelligence & Information Retrieval lab, KU Leuven

Topic: (When) do we still need self-attention?

4 December

Prof. Dr. Heiko Hamann

Cyber-physical Systems, Uni Konstanz

Topic: Swarm Robotics and Human-Swarm Interaction: Scalability, Minimizing Surprise, and Time-Perception

5 December

Prof. Dr. Katharina Morik

Lamarr Institute for Machine Learning and Artificial Intelligence

Topic: Machine Learning and Sustainability

19 December

Mathematics of Machine Learning, CAIDAS, JMU Würzburg

Topic: It begins with a boundary: Robustness on the interface of geometry and probability

16 January

Prof. Dr. Petra Mutzel

Chair of Computational Analytics, Uni Bonn

Topic: Algorithmic Data Science on Graphs

30 January

Prof. Dr. Daniel Loebenberger

Department of Electrical Engineering, Media and Computer Science, OTH Amberg-Weiden

Topic: Attack Surfaces Created by Generative AI

6 February

Prof. Dr. Ciro Cattuto

ISI Foundation, Torino

Topic: Network science and Machine Learning for high-resolution human proximity data

20 February

Chair of High resolution optical microscopy, Rudolf Virchow Center, JMU Würzburg

Topic: Deep learning for microscopy, microbiology and epidemiology

27 February

Dr. Matthias Fey

TU Dortmund

Topic: Large-Scale Machine Learning on Graphs