Jason Poulos
Human Frontier Collective Specialist at Scale AI
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolJason Poulos is an independent researcher and machine learning specialist with 11 years of experience at the intersection of ML, causal inference, and policy, currently designing domain-specific evaluations for frontier AI at Scale AI. He holds a Ph.D. in Political Science with a Designated Emphasis in Computational Science and Engineering from UC Berkeley and completed postdoctoral work applying transformers and causal methods in clinical and observational health settings at Brigham and Women’s Hospital and Harvard Medical School. His research portfolio includes multi-valued treatment causal methods, Bayesian frameworks for adversarial ML, and deep-learning approaches to missing-data imputation and counterfactual prediction, bridging methodological rigor with practical evaluation design. Based in Boston, he translates safety concerns into measurable tests for large models and trains ML engineer agents by creating benchmark solutions, combining academia-grade research with hands-on benchmark engineering. An often-overlooked strength is his ability to port causal thinking into domain-specific evaluation tasks, making complex policy-relevant questions machine-testable.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Political Science with a Designated Emphasis in Computational Science and Engineering, Doctor of Philosophy - PhD Political Science with a Designated Emphasis in Computational Science and Engineering at University of California, BerkeleyBachelor of Arts - BA Economics, Bachelor of Arts - BA Economics at University of Massachusetts Amherst
Github Skills (45)
representation-learning10
causal-discovery10
r-package10
ocr10
machine-learning10
imputation10
recurrent-neural-networks10
causal-inference10
deep-learning10
stock-prediction10
python9
regression9
longitudinal-data8
causal8
principal-component-analysis8
Programming languages (5)
Github contributions (5)
jvpoulos/drnns-prediction
Oct 2016 - Oct 2017
Deep Recurrent Neural Networks (RNNs) for Time-Series Prediction
Contributions:196 commits, 170 pushes, 3 branches in 1 year
recurrent-neural-networkstime-seriesrnnstime-series-predictionnews-headlines
jvpoulos/jvpoulos.github.com
Dec 2016 - Jan 2025
Contributions:164 pushes in 8 years 2 months
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