Current · Rosalind
Accelerating empirical science
My work focuses on AI for scientific discovery.
About RosalindResearcher at OpenAI
AI for scientific discovery.
I’m a researcher on the Rosalind team at OpenAI. My current focus is AI for science—how AI can accelerate discovery in biology, medicine, and empirical science.
My former UC Davis email is no longer active. Please reach out on X or LinkedIn.

Before OpenAI, I was a tenure-track assistant professor at UC Davis (2024–2025) and Purdue University (2021–2024). I received my PhD from MIT’s Institute for Data, Systems, and Society, and bachelor’s degrees in Computer Science and Economics from Tsinghua University.
My previous industry research experience includes a visiting research role at Microsoft and a research internship at Facebook Core Data Science.
Research
Current · Rosalind
My work focuses on AI for scientific discovery.
About RosalindPreviously · Safety Training
Previously, I worked on OpenAI’s Safety Training team, contributing to a shift from refusal-based training toward safe completions: making model responses helpful while respecting safety constraints.
Read about safe completionsEarlier research
Previously, I worked as an interdisciplinary researcher at the intersection of AI and empirical science, publishing in general science journals, business-school journals, and computer science conferences.
My earlier work explored social and organizational networks, causal inference and online experiments, and the use of large language models in social science.
2026
OpenAI · Research preprint
2025
OpenAI · Technical report
A safety-training paradigm focused on helpful responses that stay within safety constraints.
2025
2025
2023
PNAS · 120(51), e2310431120
2022
2018
Nature Communications · 9, 4704
2026
Information Systems Research · Published online February 2026
2026
Management Science · Published online April 2026
2025
Manufacturing & Service Operations Management · 27(6), 1832–1850
2024
Management Science · 70(7), 4465–4479 · Online 2023
2024
2023
ACM Web Conference (WWW)
2023
ACM Economics and Computation (EC) · Conference version
2022
ACM SIGecom Exchanges · 20(1), 70–72 · Reading list
2021
The Web Conference (WWW) · Conference version
2016
IEEE International Conference on Big Data · 96–105
Preprints and manuscripts from my earlier research. Conference and journal versions are linked together above.
2026
Working paper · Revised May 2026
A field experiment studying how prosocial incentives and nudges can encourage physical activity.
2024
* Equal contribution. Conference versions are identified separately from their journal extensions.