Summary
Ben Glicksberg is a leader at the intersection of health data science and machine learning, currently serving as Chief for Innovation and Entrepreneurship and founding director roles at Mount Sinai, with nine years of experience translating multi-omic patient data into precision medicine. He develops and deploys ML methods that fuse EHRs, clinical text, genomics, waveforms, and images for predictive modeling, phenotyping, drug repurposing and discovery, and has a track record of converting messy real-world clinical data into evidence suitable for regulatory use. Ben champions reproducibility and generalizability through open-source tools built on the OMOP common data model (e.g., romop.ucsf.edu and patientexplorer projects) and bridges academic research with startups as an advisor and co-founder across multiple health tech companies. Trained as a neuroscientist with a PhD and a clinical informatics postdoc, he combines deep domain expertise with product-minded execution, often steering cross-disciplinary teams toward clinically actionable insights. An unusual strength is his sustained focus on federated and scalable clinical ML workflows that preserve privacy while enabling multi-center discovery.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Neurobiology and Neurosciences, Doctor of Philosophy (Ph.D.) Neurobiology and Neurosciences at Icahn School of Medicine at Mount Sinai
Post-doc Clinical Informatics, Post-doc Clinical Informatics at University of California, San Francisco
BA Neuroscience, BA Neuroscience at Skidmore College