Brian Hie

Brian Hie is an Assistant Professor of Chemical Engineering at Stanford University, a Dieter Schwarz Foundation Stanford Data Science Faculty Fellow, and an Innovation Investigator at Arc Institute. He leads the Laboratory of Evolutionary Design, focusing on the intersection of biology and machine learning. His prior roles include a Stanford Science Fellow in the Stanford University School of Medicine and a Visiting Researcher at Meta AI.

Education:

• Ph.D., Electrical Engineering and Computer Science, Massachusetts Institute of Technology (2021)
• Bachelor’s Degree, Stanford University

Research Interests:
Brian’s work bridges machine learning and computational biology, with a focus on protein engineering, single-cell RNA sequencing, and viral evolution. His Evolutionary velocity framework predicts protein evolutionary dynamics across timescales, while his Scanorama algorithm enables efficient integration of heterogeneous single-cell datasets. He also develops structure-informed language models for antibody optimization and uncertainty-aware ML for biological discovery.

Publication Trends:
His recent work (2023) emphasizes structure-based inverse folding for antibody evolution, evolutionary scale modeling, and unsupervised optimization. Earlier studies (2022-2021) cover evolutionary velocity, multi-modal single-cell analysis, and viral escape prediction using natural language analogies.

Scientific Awards:

• Stanford Science Fellow (2021)
• National Defense Science and Engineering Graduate Fellowship (2019)

Advising: He mentors doctoral students including Brandon Ameglio, Garyk Brixi, and Chang M. Yun, with a focus on biological design and computational methods.

Labs & Collaborations:
His lab collaborates with Bio-X and the Institute for Human-Centered Artificial Intelligence (HAI), and he maintains affiliations with Sarafan ChEM-H and Stanford Data Science.