Science accelerates when AI meets deep domain expertise.
I'm a Research Scientist at ByteDance Seed. I earned my Ph.D. in quantum chemistry with Laura Gagliardi at the University of Minnesota, developing quantum embedding methods for materials, then did a postdoc with David Reichman at Columbia on auxiliary-field quantum Monte Carlo for periodic solids. Since joining ByteDance in 2022, I've worked on generative AI for reaction chemistry, high-throughput scientific data pipelines, and FEMION, a GPU-accelerated embedding framework for metals.
I build at the intersection of AI and science, combining modern deep learning and agentic AI with high-fidelity ab initio data from quantum chemistry to reveal hidden chemical transformations that drive progress in drug development, materials design, energy, and beyond. Outside fundamental research, I bring the same AI + Science mindset to real-world problems, creating systems that bring AI into new fields to boost productivity. From agentic workflows to intelligent tools, if AI can make something faster, smarter, or more impactful, I want to build it.