Munich AI Lectures

Part 2: Learning, Reasoning and Optimisation: Adversarial Robustness of Neural Networks

Holger Hoos, RWTH Aachen University

   17.12.2024

   5:30 pm - 7:00 pm

   Senatssaal, LMU Munich Geschwister-Scholl-Platz 1 Munich

In the second part of the event, Holger Hoos will present an introduction to neural network robustness, focusing on robustness verification and local robustness distributions. He will illustrate these concepts with examples from image and audio classification and discuss their implications for bias, fairness, and the development of safe, dependable, and sustainable AI.

About Holger Hoos

Holger H. Hoos holds an Alexander von Humboldt professorship in AI at RWTH Aachen University (Germany), where he also leads the AI Center, as well as a professorship in machine learning at Universiteit Leiden (the Netherlands) and an adjunct professorship in computer science at the University of British Columbia (Canada). He is a Fellow of the Association of Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI) and the European AI Association (EurAI), past president of the Canadian Association for Artificial Intelligence, former editor-in-chief of the Journal of Artificial Intelligence Research (JAIR) and chair of the board of CLAIRE, an organization that seeks to strengthen European excellence in AI research and innovation (claire-ai.o)