主持人：眭亚楠 助理教授（Assistant Professor- Yanan Sui)

报告摘要：

 This talk describes ongoing research at Caltech on integrating learning into the design of safety-critical controllers for dynamical systems. To achieve control-theoretic safety guarantees while using powerful function classes such as deep neural networks, we must carefully integrate conventional control principles with learning into unified frameworks. Two paradigms will be presented: integration in dynamics modeling and integration at the policy/controller design. A special emphasis will be placed on methods that both admit relevant safety guarantees and are practical to deploy.

报告人简介：

Yisong is the director of the DOLCIT (Decision, Optimization, and Learning at the California Institute of Technology) center, which is broadly centered around research pertaining statistical decision theory, statistical machine learning, and optimization. Yisong is also on the Scientific Committee for Caltech's new Center for Autonomous Systems and Technology.

Yisong's research interests are centered around machine learning, and in particular getting theory to work in practice. To that end, his research agenda spans both fundamental and applied pursuits.