Jacob Clarysse

PhD student

I am a PhD candidate at the Department of Computer Science of ETH Zürich. Prior to starting my PhD, I got my master degree in electrical engineering and information technology at ETH Zürich.


  1. How robust accuracy suffers from certified training with convex relaxations
    Piersilvio De Bartolomeis, Jacob Clarysse, Amartya Sanyal, and Fanny Yang
    NeurIPS Workshop on empirical falsification (Long Talk) 2022
  1. Margin-based sampling in high dimensions: When being active is less efficient than staying passive
    Alexandru Tifrea*, Jacob Clarysse*, and Fanny Yang
    International Conference on Machine Learning (ICML), 2023
  2. Why adversarial training can hurt robust accuracy
    Jacob Clarysse, Julia Hörrmann, and Fanny Yang
    International Conference on Learning Representations (ICLR), 2023

Research interests

Currently, my main interest is in various theoretical perspectives and methods concerning trustworthy machine learning, ranging from classical common image corruptions to adversarial robustness and compositions thereof. To be extended.

Blog posts

Comming soon!

Contact information

jacobcl@inf.ethz.ch CAB E62.1 ETH Zürich