I am a junior research group leader (equivalent to assistant professor) at the Weierstrass Institute for Applied Analysis and Stochastics, Berlin. Prior to coming to Berlin, I worked as a postdoctoral researcher in machine learning at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. My Ph.D. study was in optimization, with William Hager at the University of Florida. See here for a short bio.
Positions and opportunities:
- New opening: fully-funded Ph.D. position in optimization and machine learning
- Other funding opportunities in Berlin:
News and updates
My big goal is to advance research in computational algorithms, in order to change the world for the better. In general, I am interested in optimization, machine learning, dynamical systems, decision-making, and control. On one hand, I am motivated by addressing the lack of robustness and data distribution shift issues in modern learning algorithms. On the other hand, I am interested in interfacing dynamical systems (e.g., gradient flow, dynamic optimal transport, control theory) and machine learning, aiming at building robust and scalable optimization and learning algorithms. Some example topics include
- machine learning, robust learning under distribution shift
- distributionally robust optimization, optimization under uncertainty
- applications of optimal transport, gradient flow, and kernel methods
- numerical optimization, numerical methods
- control, multi-stage decision-making
- data-driven modeling of dynamical systems and physics
See here for more information about research topics.
I also write a non-research blog here. Though the frequency of updates depends on how busy I am at the moment.