I am an independent researcher whose work lies at the intersection of machine learning, causal inference, and policy. I hold a Ph.D. in Political Science with a Designated Emphasis in Computational Science and Engineering from UC Berkeley and have held postdoctoral appointments in machine learning and data science.
My current research evaluates frontier AI models by designing evaluation frameworks that measure model capabilities and translate safety concerns into measurable tests. I have published studies on causal inference with multi-valued treatments, Bayesian frameworks for adversarial machine learning, and deep learning-based missing-data imputation and counterfactual prediction.
Most recent publications on Google Scholar.
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, Alexander G. Shaw, Nicholas Carlini, Boxuan Li, Harsh Raj, Ivan Bercovich, Lin Shi, Jeong Y. Shin, Thomas Walshe, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, E. K. Buchanan, Jenia Jitsev, Marianna Nezhurina, Di Lu, Orfeas M. Mastromichalakis, ..., Ludwig Schmidt.
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Chen Bo Calvin Zhang, Mohamed Shaaban, John Ling, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, Adam Khoja, Ryan Kim, Richard Ren, Jason Hausenloy, Oliver Zhang, Mantas Mazeika, ..., Jason Poulos, et al.
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction
Jason Poulos
Statistics and Public Policy, 2024
Targeted Learning in Observational Studies with Multi-Level Treatments: An Evaluation of Antipsychotic Drug Treatment Safety
Jason Poulos, Marcela Horvitz-Lennon, Katya Zelevinsky, Thomas Huijskens, Pooja Tyagi, Jiaju Yan, Jordi Diaz, Tudor Cristea-Platon, Sharon-Lise Normand
Statistics in Medicine, 2024
Adversarial Machine Learning: Bayesian Perspectives
David Rios Insua, Roi Naveiro, Víctor Gallego, Jason Poulos
Journal of the American Statistical Association, 2023
Are Deep Learning Models Superior for Missing Data Imputation in Surveys? Evidence from an Empirical Comparison
Zhenhua Wang, Olanrewaju Akande, Jason Poulos, Fan Li
Survey Methodology, 2022
RNN-Based Counterfactual Prediction, with an Application to Homestead Policy and Public Schooling
Jason Poulos, Shuxi Zeng
Journal of the Royal Statistical Society (C), 2021
Character-Based Handwritten Text Transcription with Attention Networks
Jason Poulos, Rafael Valle
Neural Computing & Applications, 2021
Estimating Population Average Treatment Effects from Experiments with Noncompliance
Kellie Ottoboni, Jason Poulos
Journal of Causal Inference, 2020
Missing Data Imputation for Supervised Learning
Jason Poulos, Rafael Valle
Applied Artificial Intelligence, 2018
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, Alexander G. Shaw, Nicholas Carlini, Boxuan Li, Harsh Raj, Ivan Bercovich, Lin Shi, Jeong Y. Shin, Thomas Walshe, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, E. K. Buchanan, Jenia Jitsev, Marianna Nezhurina, Di Lu, Orfeas M. Mastromichalakis, ..., Ludwig Schmidt.
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Chen Bo Calvin Zhang, Mohamed Shaaban, John Ling, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, Adam Khoja, Ryan Kim, Richard Ren, Jason Hausenloy, Oliver Zhang, Mantas Mazeika, ..., Jason Poulos, et al.
Revisiting Diabetes Risk of Olanzapine versus Aripiprazole for Serious Mental Illness Care
Denis Agniel, Sharon-Lise Normand, John Newcomer, Katya Zelevinsky, Jason Poulos, Jeannette Tsuei, Marcela Horvitz-Lennon
BJPsych Open, 2024
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction
Jason Poulos
Statistics and Public Policy, 2024
Targeted Learning in Observational Studies with Multi-Level Treatments: An Evaluation of Antipsychotic Drug Treatment Safety
Jason Poulos, Marcela Horvitz-Lennon, Katya Zelevinsky, Thomas Huijskens, Pooja Tyagi, Jiaju Yan, Jordi Diaz, Tudor Cristea-Platon, Sharon-Lise Normand
Statistics in Medicine, 2024
Antipsychotics and the Risk of Diabetes and Death among Adults with Serious Mental Illnesses
Jason Poulos, Sharon-Lise Normand, Katya Zelevinsky, John Newcomer, Denis Agniel, Haley Abing, Marcela Horvitz-Lennon
Psychological Medicine, 2023
Adversarial Machine Learning: Bayesian Perspectives
David Rios Insua, Roi Naveiro, Víctor Gallego, Jason Poulos
Journal of the American Statistical Association, 2023
Gender Gaps in Frontier Entrepreneurship? Evidence from 1901 Oklahoma Land Lottery Winners
Jason Poulos
Journal of Historical Political Economy, 2023
Are Deep Learning Models Superior for Missing Data Imputation in Surveys? Evidence from an Empirical Comparison
Zhenhua Wang, Olanrewaju Akande, Jason Poulos, Fan Li
Survey Methodology, 2022
RNN-Based Counterfactual Prediction, with an Application to Homestead Policy and Public Schooling
Jason Poulos, Shuxi Zeng
Journal of the Royal Statistical Society (C), 2021
Character-Based Handwritten Text Transcription with Attention Networks
Jason Poulos, Rafael Valle
Neural Computing & Applications, 2021
Amnesty Policy and Elite Persistence in the Postbellum South: Evidence from a Regression Discontinuity Design
Jason Poulos
Journal of Historical Political Economy, 2021
Estimating Population Average Treatment Effects from Experiments with Noncompliance
Kellie Ottoboni, Jason Poulos
Journal of Causal Inference, 2020
Land Lotteries, Long-Term Wealth, and Political Selection
Jason Poulos
Public Choice, 2019
Missing Data Imputation for Supervised Learning
Jason Poulos, Rafael Valle
Applied Artificial Intelligence, 2018
Full CV: PDF.