Jonathan Lam is a data scientist with a PhD in Biomedical Informatics from UC San Diego and nine years of experience applying machine learning to clinical problems, particularly multimodal EHR data. He has built and deployed AI-driven clinical decision support models for the ICU as Lead Data Scientist at Healcisio and now applies that expertise at the U.S. Department of Veterans Affairs. His background in theoretical condensed matter physics and machine learning during graduate work gives him a strong quantitative foundation and a knack for translating complex models into robust clinical tools. Jonathan’s blend of academic research (Shamim Nemati Lab), industry internships in pharma and medtech, and hands-on production experience positions him to bridge research and operational healthcare AI. He also brings interdisciplinary training from a BS in Neurobiology with minors in chemistry and math, which informs his approach to biologically grounded modeling. Colleagues describe him as someone who pairs rigorous theory with practical deployment—making sophisticated algorithms usable at the bedside.
9 years of coding experience
9 years of employment as a software developer
Bachelor of Science - BS, Neurobiology, Minor in Chemistry and Mathematics, Bachelor of Science - BS, Neurobiology, Minor in Chemistry and Mathematics at University of Washington
University of California, San Diego
High School Diploma, High School Diploma at Mission San Jose High School
Contributions:4 PRs, 6 pushes, 4 branches in 1 month
first-repository
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