I am a junior research group leader (similar to assistant professor in North America) at the Data-driven Optimization and Control Group, Weierstrass Institute for Applied Analysis and Stochastics, Berlin. I am also an affiliated researcher at the Empirical Inference Department, Max Planck Institute for Intelligent Systems, Tübingen.
Positions and Opportunities:
Ph.D. position in Berlin, Germany on robust machine learning and robust optimization
- [Accepting applications] Postdoc position at Weierstrass Institute, Berlin, the intersection of mathematical optimization, machine learning, optimal control
- Additional funding opportunities:
I write a blog here. Though the freqency of updates depends on how busy I am at the moment.
In general, I am an applied mathematician interested in optimization, machine learning (with a focus on distributional robustness), function spaces, dynamical systems, and control. My group focuses on the mathematical optimization foundations for machine learning, dynamical systems, and control algorithms, and, more broadly, data-driven algorithmic decision-making. We are especially motivated by addressing the lack of robustness and data distribution shift issues in modern learning algorithms, as well as interfacing dynamical systems and machine learning.
- Machine learning, kernel methods, robust learning under distribution shift
- Distributionally robust optimization, stochastic optimization
- Dynamical systems, control, multi-stage decision-making
- Numerical optimization, numerical analysis, numerical optimal control