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Sheng Wang

Sheng Wang

Research focus

computational biomedicine, machine learning, natural language processing


Ph.D. Computer Science, University of Illinois at Urbana-Champaign, 2018
B.S. Computer Science, Peking University, 2013

Sheng Wang joins the Allen School from Stanford University where he held a postdoctoral appointment in the School of Medicine and was a Chan Zuckerberg Biohub Scholar.

In his research, Sheng uses machine learning and natural language processing to advance biomedical discovery, for example predicting novel cell types and discovering new functions of a novel gene set. His computational approaches advance representation, classification and interpretation of never-before-seen biomedicine.

He is currently developing new methods to predict and understand novel classes and cohorts in biomedicine, including studying sparsely annotated protein functions, novel cell types and rare diseases. His research has influenced work in biology, medicine and healthcare, and is in use at biomedical institutions including Chan Zuckerberg Biohub, NIH National Center for Advancing Translational Sciences and the Mayo Clinic. He has received many honors including best paper awards and fellowships from the AMIA 2020 Year in Review, ISMB, C.L. and Jane W.S. Liu Award, and the 3-M Foundation.