王捷

助理教授

教育背景

佐治亚理工学院博士（2020-2025）

香港中文大学（深圳）学士（2016-2020）

学术领域
人工智能, 计算机科学, 机器学习与人工智能, 运筹学, 优化算法, 应用概率与随机系统, 统计学, 统计理论, 统计计算和大数据分析
研究领域
优化与统计以及在机器学习领域里的应用
个人网站
https://walterbabyrudin.github.io/
个人简介

王捷博士于2025年在佐治亚理工学院工业工程系获得博士学位。他的研究结合统计学与优化方法，聚焦于不确定性下的决策问题，并广泛应用于机器学习、医疗健康、运筹管理和无线通信等领域。他的研究成果发表在多个顶级期刊和会议上，包括《Operations Research》，《Information and Inference: a Journal of the IMA》，《IEEE Journal on Selected Areas in Communications》，《IEEE Journal on Selected Areas in Information Theory》，《NeurIPS》，《ICML》和《AISTATS》。他曾获得多项荣誉，包括2022年INFORMS海报竞赛冠军、2022年工业工程系Robert Goodell Brown研究卓越奖、2023年INFORMS数据挖掘与决策分析研讨会最佳理论论文奖、2023年INFORMS数据挖掘学会数据竞赛入围奖、2024年INFORMS计算学会最佳学生论文奖亚军、2024年INFORMS数据挖掘学会学生论文奖亚军、2024年INFORMS数据挖掘学会数据竞赛冠军。

学术著作

Journal articles

1. “Reliable Off-policy Evaluation for Reinforcement Learning”, Operations Research, 72(2): 699-716, 2024 (with R. Gao and H. Zha).

2. “A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks”, Information and Inference: A Journal of the IMA, 12(3): 1867-1897, 2023 (with M. Chen, T. Zhao, W. Liao and Y. Xie).

3. “On Achievable Rates of Line Networks with Generalized Batched Network Coding”, IEEE Journal on Selected Areas in Communications, vol. 42, no. 5, pp. 1316-1328, May 2024 (with S. Yang, Y. Dong and Y. Zhang).

4. J. Wang, R. Gao and Y. Xie. “Sinkhorn distributionally robust optimization”, Under Major Revision at Operations Research.

5. Y. Hu, J. Wang. X. Chen and N. He. “Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles”, Under Major Revision at a UTD Journal.

Conference articles

1. “Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances”, International Conference on Machine Learning, 2025 (with M. Boedihardjo, Y. Xie).

2. “Contextual stochastic bilevel optimization”, Advances in Neural Information Processing Systems, pp. 78412-78434, 2023 (with Y. Hu, D. Kuhn, A. Krause and Y. Xie).

3. “Improving Sepsis Prediction Model Generalization With Optimal Transport”, Machine Learning for Health, pp. 474-4885, 2022 (with R. Moore, Y. Xie and R. Kamaleswaran).

4. “Two-sample Test with Kernel Projected Wasserstein Distance”, International Conference on Artificial Intelligence and Statistics, pp. 8022-8055, 2022 (with R. Gao and Y. Xie).

5. “Two-sample Test using Projected Wasserstein Distance”, IEEE International Symposium on Information Theory, pp. 3320-3325 (with R. Gao and Y. Xie).

更多已出版著作，请点击https://walterbabyrudin.github.io/publication.html 查看