Wei Li is an associate professor and computational biologist with 14 years of experience designing algorithms at the intersection of AI, gene editing, and next-generation sequencing for pediatric disease and cancer. He developed widely adopted CRISPR screening analysis tools (100k+ downloads, ~2000 citations) and builds machine learning/deep learning models for Cas9/Cas13 and base editors, as well as RNA-seq assembly methods. His work spans method development and close wet-lab collaboration to elucidate functions of genes and noncoding elements in cancer, viral infection, and pediatric disorders. Trained as a computer scientist (Ph.D., UC Riverside) with postdoctoral and research fellowships at Harvard and Dana-Farber, he blends rigorous algorithmic design with practical translational impact in clinical genomics. An uncommon strength is his track record of shipping both foundational open-source tools and predictive models that are routinely used by experimentalists.
14 years of coding experience
12 years of employment as a software developer
Ph.D, Computer Science, Ph.D, Computer Science at University of California, Riverside
Master of Science (M.S.), Computer Science and Engineering, Master of Science (M.S.), Computer Science and Engineering at Tsinghua University
Contributions:19 commits, 22 pushes, 1 comment in 8 years
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