I am a fifth-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of Washington, advised by Prof. Baosen Zhang.

My research interests are in area of cyber-physical and energy systems, from the perspective of machine learning, optimization, and control. During my Ph.D. studies, I developed algorithms for controlling and optimizing resources in energy systems and discovered fundamental, societal-scale insights in data-driven control systems. My work has been applied by Microsoft, Doosan Gridtech, Centrica, JD.com and DeepMind.


[2020/04] Two new preprints on “Input Convex Neural Networks for Optimal Voltage Regulation” and “Safe Reinforcement Learning” are on arXiv!

[2020/03] Our work “Robust Reinforcement Learning for Continuous Control with Model Misspecification” will appear in ICLR 2020! [PDF]

[2020/02] Invited talk at Purdue ECE.

[2020/02] Invited talks at UCSD ECE and Penn State EECS.

[2020/01] Invited talk at Caltech CMS.

[2019/12] Two works Data-driven Robust RL and Learning Neural Simulators are presented in NeurIPS 2019 Workshop on Safety and Robustness in Decision Making. [Poster1] [Poster2]

[2019/05] Our work “Optimal Control Via Neural Networks: A Convex Approach’’ is presented in ICLR 2019! Poster and source code could be found here. [PDF] [Poster] [Code]

[2019/04] I will join DeepMind, London as a research scientist intern this summer!

[2019/03] I am invited to attend the NSF iREDEFINE workshop in Tucson, Arizona, and present my research! The NSF iREDEFINE award is given to support diversity in ECE faculty.

[2018/10] I am named a Rising Stars in EECS (2018) by MIT. It’s so glad to meet all these amazing and talented women EECS graduate students and postdocs interested in exploring careers in academia!