Building machine learning that is useful to science.

I am a PhD researcher in Materials Science and Engineering at Cornell University, working with Prof. Jingjie Yeo. My research sits at the intersection of machine learning and computational materials science.

I develop generative and data-centric methods for scientific discovery: crystal structure prediction, machine-learning interatomic potentials, atomistic structure identification, and analysis tools for STEM imaging and spectroscopy.

Before Cornell, I worked on scanning transmission electron microscopy with Prof. Wu Zhou at the University of Chinese Academy of Sciences. I also conducted research on universal materials discovery in Prof. Gerbrand Ceder's group at UC Berkeley and on crystal structure identification with Prof. Rodrigo Freitas during an exchange at MIT.

Alongside research, I build open scientific tools. I lead the development of DeepSTEM, an AI-assisted platform intended to make advanced electron-microscopy analysis more accessible and reproducible.