I am an Assistant Professor of Information Systems at the Naveen Jindal School of Management, UT Dallas. I received my PhD in Information, Risk and Operations Management from the McCombs School of Business, UT Austin in 2024, advised by Maytal Saar-Tsechansky. I received my master’s degree in Statistics from the University of Michigan and my bachelor’s degree in Statistics from the School of the Gifted Young at USTC. I previously worked at Netflix Research (advised by James McInerney and Nathan Kallus), HBS (advised by Himabindu Lakkaraju), IBM Research (advised by Wei Sun, Max Biggs, and Markus Ettl), Tencent, and Amazon.
Research
- Human-AI collaboration. How should AI and humans make decisions together effectively?
- AI agents and digital twins. Simulating decision makers with AI agents, measuring when those simulations can be trusted, and evaluating their implications.
- Data evaluation, privacy, and reliable decision making. How data can be valued, priced, and shared, and how can we make robust, reliable, and privacy-aware decisions.
Recent News
- I joined the editorial board of Decision Sciences for its department on Agentic AI and Human-Agent Collaboration in Business.
- New preprint Non-Standard Errors in AI Agents!
- New preprints Computational Copyright, Offline Consumer Surplus Estimation, and LLM-Informed Bandit!
- Our paper Sell Data to AI Algorithms Without Revealing It won the Best Paper Award at the INFORMS Workshop on Data Science 2025 and the Best Student Paper Award at WITS 2025!
- My dissertation, Advancing Human-AI Systems: On Robustness, Decision Making, and Beyond, was named Runner-Up for the INFORMS ISS Nunamaker-Chen Dissertation Award (2025).
- I received the New Faculty Research Grant from the Jindal School of Management (2 of 11 proposals funded, 2025).
- Our paper HR-Bandit: Human-AI Collaborated Linear Recourse Bandit is accepted at AISTATS 2025!
- Our paper Confounding-Robust Deferral Policy Learning is accepted at AAAI 2025!
- Our paper SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection is accepted at NeurIPS 2024 and won the Best Paper Runner-Up Award (2nd of 243 accepted papers) at WITS 2024!
- Our paper Adjusting Regression Models for Conditional Uncertainty Calibration is accepted at Machine Learning (Special Issue on Uncertainty Quantification)!
- I joined the Naveen Jindal School of Management at UT Dallas as an Assistant Professor (August 2024).
Selected Publications
* Equal contribution (alphabetical order). See the Publications page for the full list, including papers under review.
R Gao, M De-Arteaga, M Saar-Tsechansky. Learning Complementary Policies for Human-AI Deferral Collaboration. Major revision at Management Science. (Best Student Paper at CIST 2022)
Y Yang, R Gao, Z Zheng. Sell Data to AI Algorithms Without Revealing It: Secure Data Valuation and Sharing via Homomorphic Encryption. Major revision at Management Science. (Best Paper at INFORMS Workshop on Data Science 2025, Best Student Paper at WITS 2025)
M Biggs*, R Gao*, W Sun*. Loss Functions for Discrete Contextual Pricing with Observational Data. Under review at Manufacturing & Service Operations Management.
J Cao*, R Gao*, E Keyvanshokooh*, J Ma*. LIBRA: Language Model Informed Bandit Recourse Algorithm for Personalized Treatment Planning. Under review at Manufacturing & Service Operations Management.
R Gao, M Yin, J McInerney, N Kallus. Adjusting Regression Models for Conditional Uncertainty Calibration. Machine Learning, 2024.
J Cao*, R Gao*, E Keyvanshokooh*. HR-Bandit: Human-AI Collaborated Linear Recourse Bandit. AISTATS 2025.
R Gao, M Yin. Confounding-Robust Deferral Policy Learning. AAAI 2025.
R Gao, M Yin, M Saar-Tsechansky. SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection. NeurIPS 2024.
R Gao, H Lakkaraju. On the Impact of Algorithmic Recourse on Social Segregation. ICML 2023.
Z Wang*, R Gao*, M Yin*, M Zhou, D Blei. Probabilistic Conformal Prediction Using Conditional Random Samples. AISTATS 2023.
R Gao, M Saar-Tsechansky, M De-Arteaga, L Han, MK Lee, M Lease. Human-AI Collaboration with Bandit Feedback. IJCAI 2021.
Awards and Fellowships
- Best Paper Award, INFORMS Workshop on Data Science 2025.
- Best Student Paper Award, WITS 2025.
- Nunamaker-Chen Dissertation Award, Runner-Up, INFORMS Information Systems Society, 2025.
- New Faculty Research Grant (2 of 11 awarded), Naveen Jindal School of Management, UT Dallas, 2025.
- Best Paper Runner-Up Award (2nd of 243 accepted papers), WITS 2024.
- Best Student Paper Award (1 out of ~200), CIST 2022.
- PhD Incubator Special Recognition Award Finalist, INFORMS Advances in Decision Analysis Conference, 2022.
- INFORMS Data Science Workshop Scholarship, 2022 and 2023.
- UT Austin Graduate School Continuing Fellowship, 2022-2023 (competitive fellowship, one nomination per department).
- UT Austin Graduate School (OGS) Professional Development Award and Good Systems Student Conference Grant, 2020.
- UT Austin Graduate School (OGS) Provost Fellowship, 2018.
Professional Service
- Editorial Board Member, Decision Sciences (department on Agentic AI and Human-Agent Collaboration in Business), 2026-present.
- Journal reviewer: Management Science, Information Systems Research, MIS Quarterly, Operations Research, INFORMS Journal on Computing, IEEE TPAMI, Scientific Reports.
- Program committee member and reviewer, ML/AI conferences: NeurIPS, ICML, ICLR, AISTATS, AAAI, FAccT, WACV.
- Reviewer, IS conferences: WITS, ICIS, INFORMS Workshop on Data Science.