Chirag Nagpal
San Francisco, California, United States
Summary
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SeniorChirag Nagpal is a Senior AI Research Scientist based in the San Francisco Bay Area, holding a PhD in Machine Learning for Healthcare from Carnegie Mellon University. He blends traditional statistical methods—graphical models, causal inference and survival analysis—with cutting-edge deep learning to advance healthcare ML. His career spans senior roles at Google and Meta, along with impactful internships at IBM Research and JP Morgan AI Research where he worked on safety, robustness, and responsible AI for health and finance applications. Notable work includes Deep Cox Mixtures for Survival Regression and semi-parametric mixture models for censored outcomes, with publications at MLHC and NeurIPS AI in Finance. He currently leads post-training initiatives on Llama at Meta, building scalable, reliable foundation models, following impactful health ML work at Google. With about 10 years of research experience, he has a proven track record of translating theory into production-ready AI systems.
11 years of coding experience
Github Skills (92)
python10
lime10
lda10
fasttext10
regression10
deep-learning10
glove10
word2vec10
corpus10
scikit10
statistics10
graphical-models10
ai10
topic-modeling10
gensim10
Programming languages (5)
Github contributions (5)
chiragnagpal/chiragnagpal.github.io
Jan 2015 - Mar 2025
Contributions:76 pushes in 10 years 3 months
autonlab/auton-survival
Apr 2020 - Nov 2022
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
Contributions:70 reviews, 354 commits, 42 PRs in 2 years 7 months
pythonxaiphenotypingtime-seriesdata-science
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