About me

I am currently a Senior Scientist at Schrödinger, Inc. Prior to this position, I was a Postdoctoral Researcher in Lawrence Berkeley National Lab, working with Prof. Kristin Persson. I received my M.S. in Chemical Engineering at Rutger University in 2014, where I worked with Prof. Alexander Neimark to simulate the interactions between polymers, nanoparticles and solvents using Monte Carlo and dissipative particle dynamics simulations. I then completed my Ph.D. in Chemical Engineering with Prof. Kesong Yang from the University of California, San Diego in 2018. My Ph.D. research mainly focused on the electronic structure and defects in complex oxides heterostructures using first-principles calculations. In addition, I developed an efficient algorithm to generate periodic grain boundary structures. I implemented this algorithm in an open-source Python library, aimsgb, and a web GUI for an easy access.

My current research focuses materials discovery and engineering using high-throughput computation and machine learning. One of my research focuses is to develop machine learning force fields to elucidate the complex battery materials systems, ultimately expediting the process of designing novel battery materials. I am also engaged in contract research projects leveraging Schrödinger’s expertise in computational platforms and artificial intelligence.

For more information, see my CV.