Scientist, Machine Learning, Active Learning And Discovery at Bristol Myers Squibb
Cambridge, Massachusetts, United States
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Summary
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Senior
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Top School
Shruthi Chari is a Machine Learning Scientist with nine years of experience who applies explainable AI and knowledge-enabled methods to optimize small-molecule drug discovery and clinical decision support. She holds a PhD in Computer Science from RPI, where her thesis and funded research (including IARPA HIATUS and the HEALS collaboration with IBM Research) produced user-centered explanation ontologies and end-to-end LLM-augmented QA systems for clinician-facing risk prediction. Her work spans text mining, NLP, knowledge graphs, and RAG techniques to synthesize explanations grounded in authoritative medical literature, and she has published across health informatics and semantic web venues. Pragmatic and detail-oriented, she combines hands-on engineering—from search stacks and full-stack development to model explainers—with rigorous research, often bridging interdisciplinary teams of cognitive and behavior scientists. Now at Bristol Myers Squibb, she focuses on explainability-driven discovery workflows, bringing a rare blend of ontology design and practical LLM synthesis to pharmaceutical ML problems.
9 years of coding experience
7 years of employment as a software developer
ICSE, ICSE at Cluny Convent High School
Engineer’s Degree Computer Science, Engineer’s Degree Computer Science at PES Institute of Technology
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Rensselaer Polytechnic Institute
Contributions:1 release, 381 commits, 396 pushes in 2 years 4 months
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Shruthi Chari - Scientist, Machine Learning, Active Learning And Discovery at Bristol Myers Squibb