Bin Chen
Professor at Michigan State University
Grand Rapids Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolBin Chen is a tenured associate professor, entrepreneur, and co-founder who translates large-scale AI and multi-omic data into therapeutic discovery, currently leading the Center for AI-Enabled Drug Discovery at Michigan State and a transcriptomics-driven startup, Bronto Therapeutics. With a PhD in Informatics and a decade of cross-sector experience spanning Stanford, UCSF, big pharma and startups, he builds machine-learning methods for integrative bioinformatics, EHR mining, and drug repurposing. His lab’s work has been published in Cell and Nature-family journals and supported by over $7M in NIH, industry, and foundation funding, reflecting both methodological rigor and translational impact. A standing member of the NIH BDMA study section, he also mentors the next generation of PIs and runs a global data-science nonprofit serving 6,000 members, underscoring his commitment to community building beyond academia. An often-overlooked thread in his career is deep cheminformatics and semantic-web work from early industry collaborations, which continues to inform his integrative, network-based approach to drug discovery.
10 years of coding experience
9 years of employment as a software developer
Ignite; The Startup Garage, Ignite; The Startup Garage at Stanford University Graduate School of BusinessDoctor of Philosophy (Ph.D.) Informatics (Track: Cheminformatics, Minor: Bioinformatics), Doctor of Philosophy (Ph.D.) Informatics (Track: Cheminformatics, Minor: Bioinformatics) at Indiana University BloomingtonB.S chemical engineering, B.S chemical engineering at Chongqing University
Github Skills (3)
ai9
big-data8
biomedical4
Programming languages (4)
Github contributions (5)
Bin-Chen-Lab/HCC_NEN
Feb 2017 - Jun 2018
Contributions:11 commits, 21 pushes, 1 branch in 1 year 3 months
Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery
Mar 2018 - Aug 2021
A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.
Contributions:35 commits, 34 pushes, 1 branch in 3 years 5 months
aibig-data
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