Research Themes
My current research interests lie at the intersection of control theory, machine learning, and optimization.
I am often motivated by real problems, but rather than specializing in one application, I aim to develop mathematical theories of control in an abstract framework and do cross-disciplinary research that leads to various applications.
Research topics are as follows:
Optimal control, regularization, and probabilistic inference (maximum entropy control/RL, control as inference)
Adaptive control integrating online optimization and optimal control (online control, regret analysis for control)
Optimal control of probability distributions (dynamical optimal transport, Schrödinger bridge, ensemble control)
Control of large-scale systems
Stochastic control theory under heavy-tailed noise
Privacy protection for control systems
