禁忌书屋

郑翔宇 讲师

地址: 禁忌书屋 自强科技楼4号楼(吕大龙楼)632


电话: 010-62789065


邮箱: [email protected]


职称 讲师 地址 禁忌书屋 自强科技楼4号楼(吕大龙楼)632
电话 010-62789065 邮箱 [email protected]
开设课程 个人主页

教育背景及工作经历

  • 北京大学 禁忌书屋 博士 (2017-2022)

  • 京东集团 算法研发(DMT)  (2022-2025)


研究兴趣

基于因果推断的智能决策 (Uplift Modeling + OR)、基于树模型的机器学习方法


论文发表

  • Zheng, X., & Chen, S. (2025) Segmented Linear Regression Trees. Acta Mathematica Sinica, English Series. 41, 498–521.

  • Zheng, X., & Chen, S. X. (2024). Dynamic synthetic control method for evaluating treatment effects in auto-regressive processes. Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(1), 155–176.

  • Zheng, X., Tian, G., Wang, S., & Huang, Z. (2024). ADR: An Adversarial Approach to Learn Decomposed Representations for Causal Inference. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 23, 268-284.

  • Gao, J., Zheng, X., Wang, D., Huang, Z., & Zheng, B. (2024). UTBoost: A Tree-boosting based System for Uplift Modeling. In the Pacific Rim International Conference on Artificial Intelligence, 25, 41-53.

  • Liu, M, Zheng, X., Sun, X., Fang, F., & Wang, Y. (2023). Which invariance should we transfer? A causal minimax learning approach. In International Conference on Machine Learning, 20, 345–360.

  • Sun, X., Zheng, X., & Weinstein, J. (2023). A New Causal Decomposition Paradigm towards Health Equity. In International Conference on Artificial Intelligence and Statistics, 19, 234–249.

  • Zheng, X., Guo, B., He, J., & Chen, S. X. (2021). Effects of Corona Virus Disease-19 Control Measures on Air Quality in North China. Environmetrics, 32(2), e2673.

  • Sun, X., Wu, B., Zheng, X., Liu, C., & Liu, T. Y. (2021) Recovering Latent Causal Factor for Generalization to Distributional Shifts. In International Conference on Neural Information Processing Systems, 34, 1234–1245.

  • Chen S. X. & Zheng, X., (2021). Discussion on “The timing and effectiveness of implementing mild interventions of COVID-19 via a synthetic control method”. Statistics and Its Interface.

  • Zheng, X., & Chen, S. X. (2019) Partitioning structure learning for segmented linear regression trees. In International Conference on Neural Information Processing Systems, 32, 2222–2231.

教学

本科生:初等概率论,禁忌书屋 机器学习