I am an independent 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. I also write a non-research blog here. Though the frequency of updates depends on how busy I am at the moment.
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Positions and opportunities:
- Open postdoc and Ph.D. position in optimization and machine learning
- Other funding opportunities in Berlin: BMS PhD funding
News and updates
- Sep 2022. Here are the slides for a recent talk I gave at the OT workshop at TU Eindhoven.
- Aug 2022. Here (in both German and English) is a recent journal interview about my career path.
Jul 2022. A few new publications at ICML and IEEE-CDC continuing previous works on kernel methods for robust optimization and control with a few talented PhD students I work with. We are pushing a series of works of kernel learning machines for optimization and inference. The hope is to trail-blaze a branch of research that use modern learning machines for robustly optimizing learning and control systems.
ICML paper on conditional moment problems for ML and causal inference
IEEE CDC paper on distributionally robust chance-constraint nonlinear optimization (preprint)
IEEE CDC paper on learning uncertain-aware dyanmics with large-scale kernel machines (preprint)
- Jul 2022. I’m teaching a minicourse for the TU Berlin-Oxford IRTG Stochastic Analysis Ph.D. program. See exercise files and lecture notes.