Publications (Google Scholar Profile)

1. J Cao*, R Gao*, E Keyvanshokooh*.
   HR-Bandit: Human-AI Collaborated Linear Recourse Bandit AISTATS 2025
2. R Gao, M Yin.
   Confounding-Robust Deferral Policy Learning AAAI 2025
3. R Gao, M Yin, M Saar-Tsechansky.
   SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection NeurIPS 2024 Best Paper Runner-Up at WITS 2024
4. R Gao, M Saar-Tsechansky, M De-Arteaga, L Han, MK Lee.
   Human-AI Collaboration with Bandit Feedback IJCAI 2021
5. L Han, MR Min, A Stathopoulos, Y Tian, R Gao, A Kadav, D Metaxas.
   Dual Projection Generative Adversarial Networks for Conditional Image Generation ICCV 2021
6. [Under Review] R Gao, M Saar-Tsechansky, M De-Arteaga, L Han, MK Lee, W Sun, M Lease.
   Learning Complementary Policies for Human-AI Teams Management Science - Major Revision Best Student Paper at CIST 2022
7. [Under Review] M Yin, R Gao, Z Cong.
   Personalizing Language Models for Generative Targeting Marketing Science - Reject and ResubmitMarketing Science Institute Grant

1. R Gao, M Yin.
   Confounding-Robust Deferral Policy Learning AAAI 2025
2. R Gao, M Yin, J McInerney, N Kallus.
   Adjusting Regression Models for Conditional Uncertainty Calibration Machine Learning 2024
3. Z Wang*, R Gao*, M Yin*, M Zhou, D Blei.
   Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023
4. R Gao, M Biggs, W Sun, and L Han.
   Enhancing counterfactual classification performance via self-training AAAI 2022
5. L Han, R Gao, M Kim, X Tao, B Liu, D Metaxas.
   Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons AAAI 2020
6. L Han, Y Zou, R Gao, L Wang, D Metaxas.
   Unsupervised domain adaptation via calibrating uncertainties CVPR Workshop 2019

1. J Cao*, R Gao*, E Keyvanshokooh*.
   HR-Bandit: Human-AI Collaborated Linear Recourse Bandit AISTATS 2025
2. R Gao, H Lakkaraju.
   On the Impact of Algorithmic Recourse on Social Segregation ICML 2023

1. R Gao, M Yin, M Saar-Tsechansky.
   SEL-BALD: Deep Bayesian Active Learning for Selective Labeling with Instance Rejection NeurIPS 2024 Best Paper Runner-Up at WITS 2024
2. R Gao, M Saar-Tsechansky.
   Cost-accuracy aware adaptive labeling for active learning AAAI 2020
3. [Working Paper] R Gao, M Saar-Tsechansky.
   Active Incentive Learning Preliminary version at CIST 2022
4. [Working Paper] Y Yang, R Gao, Z Zheng.
   Sell Data to AI Algorithms Without Revealing It: Secure Data Valuation and Sharing via Homomorphic Encryption. Preliminary version at CIST 2025 & INFORMS WDS 2025

Working Journal Papers

1. [Under Review] R Gao, M Saar-Tsechansky, M De-Arteaga, L Han, MK Lee, W Sun, M Lease.
   Learning Complementary Policies for Human-AI Teams Management Science - Major Revision Best Student Paper at CIST 2022
2. [Under Review] M Biggs*, R Gao*, W Sun*.
   Loss Functions for Discrete Contextual Pricing with Observational Data Operations Research - Major Revision
3. [Under Review] M Yin, R Gao, Z Cong.
   Personalizing Language Models for Generative Targeting Marketing Science - Reject and ResubmitMarketing Science Institute Grant
4. Y Yang, R Gao, Z Zheng.
   Sell Data to AI Algorithms Without Revealing It: Secure Data Valuation and Sharing via Homomorphic Encryption. Preliminary version at CIST 2025 & INFORMS WDS 2025
5. M Yin, R Gao, W Lin, S Shugan.
   Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design Preliminary version at RealML @ NeurIPS 2023

Patents

1. R Gao, W Sun, M Biggs, M Ettl, Y Drissi.
   Counterfactual Self-Training US Patent App. 17/402,367
2. R Gao, W Sun, M Biggs, Y Drissi, M Ettl.
   Imputing Counterfactual Data to Facilitate Machine Learning Model Training US Patent App. 17/654,617