Chuan Li

Chuan is a Principal Applied Scientist at Microsoft Research, with a focus on applying machine learning in multi-omics and pharmacology. She received her Ph.D. in Ecology and Evolutionary Biology with a dual degree in Statistics from the University of Michigan in 2017. During her Ph.D. at Dr. Jianzhi Zhang’s lab, she worked on quantifying intergenic and intragenic epistasis at a large scale with both experimental and computational approaches using yeast as the model system. She published highly influential papers on the empirical determination of the fitness landscape and fitness effects of synonymous mutations (here and here). In the Petrov lab, she develops high-throughput techniques in “A Functional Taxonomy of Tumor Suppression in Oncogenic KRAS–Driven Lung Cancer” revealing the functional taxonomy of tumor progression,“Quantitative In Vivo Analyses Reveal a Complex Pharmacogenomic Landscape in Lung Adenocarcinoma” quantifying genotype-specific therapeutic responses, and uncovering novel tumor suppressor genes. Chuan received the CEHG postdoctoral fellowship and prestigious Damon Runyon Fellowship that supported her postdoc research.