Grants per year
Personal profile
Research Interests
Professor Zhaoran’s research is at the interface of statistics and optimization in machine learning. He has specific interests in understanding the tradeoff between statistical accuracy and computational effort as well as establishing provable guarantees for non-convex problems in statistical learning.
Education/Academic qualification
Operations Research and Financial Engineering, PhD, Princeton University
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Network
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Collaborative Research: CIF: Medium: Learning to Control from Data: from Theory to Practice
10/1/22 → 9/30/26
Project: Research project
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Toward an integrative approach to machine learning for traffic management
9/1/22 → 8/31/25
Project: Research project
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Institute for Data, Econometrics, Algorithms and Learning (IDEAL)
Vijayaraghavan, A., Berry, R. A., Hartline, J. D., Khuller, S., Nocedal, J., Auerbach, E. J., Auffinger, A., Bugni, F. A., Canay, I. A., Gaudio, J., Golub, B., Guo, D., Horowitz, J. L., Hullman, J. R., Liang, A., Linna Jr., D. W., Makarychev, K., Wang, Z. & Wei, E.
9/1/22 → 8/31/27
Project: Research project
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CAREER: Principled Deep Reinforcement Learning for Societal Systems
2/1/21 → 1/31/26
Project: Research project
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Collaborative Research: CIF: Small: A Unified Framework of Distributional Optimization via Variational Transport
10/1/20 → 9/30/23
Project: Research project
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Addressing Hindsight Bias in Multigoal Reinforcement Learning
Bai, C., Wang, L., Wang, Y., Wang, Z., Zhao, R., Bai, C. & Liu, P., Jan 1 2023, In: IEEE Transactions on Cybernetics. 53, 1, p. 392-405 14 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Accelerate online reinforcement learning for building HVAC control with heterogeneous expert guidances
Xu, S., Fu, Y., Wang, Y., Yang, Z., O'Neill, Z., Wang, Z. & Zhu, Q., Nov 9 2022, BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc, p. 89-98 10 p. (BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Design-while-Verify: Correct-by-Construction Control Learning with Verification in the Loop
Wang, Y., Huang, C., Wang, Z., Wang, Z. & Zhu, Q., Jul 10 2022, Proceedings of the 59th ACM/IEEE Design Automation Conference, DAC 2022. Institute of Electrical and Electronics Engineers Inc., p. 925-930 6 p. (Proceedings - Design Automation Conference).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Fairness-Oriented Learning for Optimal Individualized Treatment Rules
Fang, E. X., Wang, Z. & Wang, L., 2022, (Accepted/In press) In: Journal of the American Statistical Association.Research output: Contribution to journal › Article › peer-review
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Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning
Bai, C., Xiao, T., Zhu, Z., Wang, L., Zhou, F., Garg, A., He, B., Liu, P. & Wang, Z., 2022, (Accepted/In press) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-15 15 p.Research output: Contribution to journal › Article › peer-review
Datasets
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Fairness-Oriented Learning for Optimal Individualized Treatment Rules
Fang, E. X. (Creator), Wang, Z. (Creator) & Wang, L. (Creator), Taylor & Francis, 2021
DOI: 10.6084/m9.figshare.17064129.v1, https://tandf.figshare.com/articles/dataset/Fairness-Oriented_Learning_for_Optimal_Individualized_Treatment_Rules/17064129/1
Dataset
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Online Bootstrap Inference For Policy Evaluation In Reinforcement Learning
Ramprasad, P. (Creator), Li, Y. (Creator), Yang, Z. (Creator), Wang, Z. (Creator), Sun, W. W. (Creator) & Cheng, G. (Creator), Taylor & Francis, 2022
DOI: 10.6084/m9.figshare.20231503, https://tandf.figshare.com/articles/dataset/Online_Bootstrap_Inference_For_Policy_Evaluation_In_Reinforcement_Learning/20231503
Dataset
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Online Bootstrap Inference For Policy Evaluation In Reinforcement Learning
Ramprasad, P. (Creator), Li, Y. (Creator), Yang, Z. (Creator), Wang, Z. (Creator), Sun, W. W. (Creator) & Cheng, G. (Creator), Taylor & Francis, 2022
DOI: 10.6084/m9.figshare.20231503.v1, https://tandf.figshare.com/articles/dataset/Online_Bootstrap_Inference_For_Policy_Evaluation_In_Reinforcement_Learning/20231503/1
Dataset