About me

Hi~ I am a Ph.D. candidate in School of Engineering and Applied Sciences (SEAS) at Harvard University, working with Prof. Na Li. I received my double B.S. degrees in engineering physics and economics from Tsinghua University in 2015, and the master degree in electrical engineering from Tsinghua University in 2017.

My research interests lie in learning, optimization, and control of human-cyber-physical systems, with emphasis applications to smart grids and smart cities. In particular, I am broadly interested in robust optimization, distributed optimization and control, online learning and human-in-the-loop control, model-free optimization and control, reinforcement learning, etc.

My C.V. is here.

Updates

[12/2021] I received the Outstanding Student Paper Award in 2021 IEEE Conference on Decision and Control (CDC) for our paper “Safe Model-Free Optimal Voltage Control via Continuous-Time Zeroth-Order Methods”.

[11/02/2021] Check our new preprint “Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters”. This is an interesting work that borrows the idea of high-pass and low-pass filters from extremum seeking control to design new single-point zeroth-order optimization algorithms with significant performance improvement.

I co-chaired a session “data-driven optimization and control for power systems” in 2021 INFORMS Annual Meeting, Oct. 24-27, Anaheim, California, USA.

[07/27/2021] Our paper “Model-Free Optimal Voltage Control via Continuous-Time Zeroth-Order Methods” was accepted for publication in 2021 60th IEEE Conference on Decision and Control (CDC).

[06/09/2021] Our paper “Online Learning and Distributed Control for Residential Demand Response” was accepted for publication in IEEE Transactions on Smart Grid.

[03/25/2021] Our new preprint on model-free control “Model-Free Optimal Voltage Control via Continuous-Time Zeroth-Order Methods” is available on Arxiv.

[03/18/2021] Our paper “Leveraging Two-Stage Adaptive Robust Optimization for Power Flexibility Aggregation” was accepted for publication in IEEE Transactions on Smart Grid.

[01/26/2021] Check our review paper on applying RL to power systems: “Reinforcement Learning for Decision-Making and Control in Power Systems: Tutorial, Review, and Vision”.

[10/11/2020] Check out our new preprint on demand response “Online Learning and Distributed Control for Residential Demand Response”.

[08/31/2020] Our paper “Distributed Automatic Load Frequency Control with Optimality in Power Systems” was accepted for publication in IEEE Transactions on Control of Network Systems.

[07/15/2020] Our paper “Online Residential Demand Response via Contextual Multi-Armed Bandits” was accepted for publication in 2020 59th IEEE Conference on Decision and Control (CDC).

[07/01/2020] Our work “Exponential Stability of Primal-Dual Gradient Dynamics with Non-Strong Convexity” was presented in 2020 American Control Conference (ACC).

[06/06/2020] Our paper “Online Residential Demand Response via Contextual Multi-Armed Bandits” was accepted for publication in The IEEE Control Systems Letters.

[06/03/2020] This new personal website said “HelloWorld”.