About me
Hi, I am Yassine.
I am a PhD Student (July 2019 - now) working on Robust Machine Learning and Learning Control at the Empirical Inference Department, Max Planck Institute for Intelligent Systems. I am advised by Jia-Jie Zhu and Bernhard Schölkopf. Before starting my PhD, I completed a Master’s degree in Robotics, Systems and Control at ETH Zürich and a Bachelor’s degree in Mechanical Engineering at ETH Zürich.
My research interests lie at the intersection of Machine Learning, Stochastic Control and Reinforcement Learning with a focus on robustness. Initially, I started working on robotics, more specifically robot table-tennis. This experience led to my interest in robust/safe learning and control approaches, specifically robustness against distribution shifts in data.
News
- I will be starting as an Applied Scientist Intern at Amazon Luxembourg in October 2023, excited to start!
- Our paper Estimation Beyond Data Reweighting: Kernel Method of Moments got accepted at ICML 2023. See you in Hawaii!
- Two papers got accepted at CDC 2022: Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee and Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics, July 2022
- I gave a tutorial on data-driven Chance-Constrained Optimization at the TU Berlin - Oxford Summer School, July 2022
- I gave a talk in an invited session at EURO2022, July 2022