My research interests lie at the intersection of control, optimization, and reinforcement learning. The range of topics includes approximate dynamic programming, model predictive control, robust and stochastic optimization, and polynomial optimization. I am particularly interested in real-time decision problems driven by forecast information, with applications in robotics, electrical power networks, and transportation systems.
- Oct 2019: Our paper "A moment and sum-of-squares extension of dual dynamic programming with application to nonlinear energy storage problems" has been accepted to European Journal of Operational Research. Link
- May 2019: We are looking for a research assistant/intern to help integrate systems for the DeepGreen robot project. More info (Update: position has been filled)
- Feb 2019: These papers on approximate dynamic programming were accepted to IEEE TAC and ECC respectively.
- Jul 2018: Served as co-examiner for Marc Hohmann, who successfully defended his PhD thesis on 2nd July. Congratulations Marc!
- Jan-May 2018: Residential fellowship at the Simons Institute for the Theory of Computing at UC Berkeley, CA, USA.
- Jan 2018: Outstanding Reviewer 2017 award from the journal IEEE Control Systems Letters.