Laying at the intersection between machine learning and energy systems, I am passionate about using data-driven approaches to enable a 100% renewable energy infrastructure and a clean and efficient electric grid.
I am currently a Ph.D. Candidate at the Department of Electrical Engineering, Stanford University and I am fortunately advised by Professor Ram Rajagopal. My primary research focus is on the data-driven modelling, optimization, and planning of electric power systems. In particular, I am applying advanced machine learning techniques to solve the emerging problems in distribution electric grids brought by the penetration of distributed energy resources, such as solar generations, battery storage and EVs. I am proud to be a member of Stanford Bits & Watts Initiative, and to be the student leader of the VADER project.
I also obtained my M.S. in Electrical Engineering at Stanford University. Before coming to Stanford, I received my B.S. in Mathematics and Physics from the Academic Talent Program at Tsinghua University.