I am a Ph.D. student in Materials Science and Engineering at Massachusetts Institute of Technology, advised by Professor Jeffrey Grossman. My research focuses on the development of machine learning algorithms for accelerating the design of new energy materials, motivated by the urgent need of material innovations for the next generation renewable energy technology. I work closely with simulation and experiment researchers from various fields, aiming to apply machine learning to real-world systems like Lithium-ion batteries and quantum dots.
Before joining MIT, I received my B.S. in Chemistry from Peking University in 2015. I was a visiting student at School of Engineering of Stanford University in 2014.
[06/2019] Our work “Graph dynamical networks for unsupervised learning of atomic scale dynamics in materials” is published on Nature Communications.
[05/2019] I joined DeepMind in London as an intern to start a project at the science team.
[02/2019] I joined X (formerly Google X) in Mountain View as an intern to work on an early stage project that combines machine learning and physics.