About Yasa Baig

Yasa Baig was born in Agra, India. With an Indian father and a Pakistani mother, his parents had been unable to build a life together in either homeland, and his family immigrated to the United States when he was one. Yasa grew up across several American communities—Buffalo, New York while his father completed medical residency, rural Emporia, Virginia, and later Foxborough, Massachusetts. Becoming a naturalized citizen near the start of high school remains one of his proudest moments, and his Muslim identity continues to shape his understanding of belonging, responsibility, and service.

Yasa's academic path has been defined by a desire to understand biological systems using rigorous quantitative tools. He studied physics and computer science at Duke University as an Angier B. Duke Scholar and Barry Goldwater Scholarship recipient, working under the mentorship of Lingchong You, where he learned how mathematical structure and computation can bring clarity to complex biological phenomena. Having grown up across a wide range of socioeconomic contexts, Yasa saw firsthand how mentorship shapes opportunity, and as an undergraduate he cofounded the Duke Applied Machine Learning Group, training hundreds of students in machine learning.

After graduation, he pursued training in theoretical biophysics and applied mathematics at the University of Cambridge as a Marshall Scholar, working with Raymond Goldstein. Trained as a physicist, equipped with the tools of computer science, and drawn to biology by curiosity, Yasa now seeks to merge the traditions of mathematical physics with recent advances in artificial intelligence to build "virtual cell" models—AI systems that organize the exponentially growing corpus of biological data into meaningful, predictive frameworks of living systems.

Yasa is currently pursuing a PhD in bioengineering at Stanford University under the joint advisement of Stephen Quake and Christopher Ré. His research focuses on developing artificial intelligence models of gene regulation and cellular behavior that transform large-scale biological data into predictive tools for discovery in medicine and biotechnology. He ultimately aspires to become a professor leading a research group that not only advances science but develops the next generation of rigorous, community-minded scientists.