副教授，硕士生导师

通讯地址：北京工商大学数学与统计学院，邮编：100048
电子信箱：pengwu@btbu.edu.cn

办公室：良乡校区楼数学与统计学院209室

个人主页：https://pengwu.site/

个人简历

2015年7月毕业于江西财经大学，获学士学位

2020年7月毕业于北京师范大学大学，获硕士学位

2022年6月，北京大学，博士后

2022年6月至今，北京工商大学，数学与统计学院，应用统计系任教

研究领域

主要研究因果推断，推荐系统，医疗决策，机器学习

主讲课程

数据挖掘，数据分析与统计软件, 随机过程

承担项目

1.基于数据融合的长期因果效应研究，国家自然科学基金青年项目，2024.1-2026.12，主持

发表的主要论文（*通讯作者）

[1] Wenjie Hu, Xiao-Hua Zhou, and Peng Wu* (2023), Identification and estimation of treatment effects on long-term outcomes in clinical trials with external observational data. Statistica Sinica

[2] Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Fuli Feng, Xiangnan He, Zhi Geng, and Peng Wu* (2023), Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 23)

[3] Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu*, and Peng Wu* (2023), Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. Fortieth International Conference on Machine Learning (ICML 23)

[4] Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu*, and Peng Cui (2023), Propensity Matters: Measuring and Enhancing Balancing for Recommendation. Fortieth International Conference on Machine Learning (ICML 23)

[5] Haoxuan Li, Quanyu Dai, Zhenhua Dong, Xiao-Hua Zhou, and Peng Wu* (2023), Multiple Robust Learning for Recommendation. Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 23, Oral)

[6] Haoxuan Li, Yan Lyu, Chunyuan Zheng, and Peng Wu* (2023), TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. Proceedings of the 11th International Conference on Learning Representations (ICLR 23)

[7] Haoxuan Li, Chunyuan Zheng, and Peng Wu* (2023), StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. Proceedings of the 11th International Conference on Learning Representations (ICLR 23)

[8] Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, and Peng Wu* (2023), Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. Proceedings of the ACM Web Conference 2023 (WWW 23, Best Student Paper Runner-up)

[9] Zhihui Yang#, Shasha Han#, Peng Wu#, Mingyue Wang, Ruoyu Li, Xiaohua Zhou, and Hang Li (2023), Modeling Posttreatment Prognosis of Skin Lesions in Patients with Psoriasis in China. JAMA Network Open. 6(4):e236795.

[10] Peng Wu, Zhiqiang Tan, Wenjie Hu, and Xiao-Hua Zhou (2022), Model-Assisted Inference for Covariate-Specific Treatment Effects with High-dimensional Data. Statistica Sinica.

[11] Peng Wu#, Shasha Han#, Xingwei Tong, and Runze Li (2022), Propensity score regression for causal inference with treatment heterogeneity. Statistica Sinica.

[12] Sihao Ding, Peng Wu*, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, and Yongdong Zhang (2022), Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. (KDD 22)

[13] Peng Wu#, Haoxuan Li#, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, and Xiao-Hua Zhou (2022), On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. International Joint Conference on Artificial Intelligence. (IJCAI 22)

[14] Quanyu Dai, Haoxuan Li, Peng Wu*, Zhenhua Dong, Xiao-Hua Zhou*, Rui Zhang, Xiuqiang He, Rui Zhang, and Jie Sun (2022), A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. (KDD 22)

[15] Peng Wu, Xinyi Xu, Xingwei Tong, Qing Jiang, and Bo Lu (2021), Semi-parametric Estimation for Average Causal Effects using Propensity Score based Spline, Journal of statistical planning and inference. 212, 153-168.

[16] Peng Wu, Xingwei Tong, Yi Wang, Jiajuan Liang, and Xiao-Hua Zhou (2021), Robust Quasi-Oracle Estimation of Average Causal Effects. Biostatistics & Epidemiology. 6(1), 144-163.

[17] Peng Wu, Baosheng Liang, Yifan Xia, and Xingwei Tong (2020), Predicting Disease Risk by Matching Quantile estimation for Censored Data, Mathematical Biosciences and Engineering. 17(5):4544-4562.

[18] Peng Wu, Qirui Hu, Xingwei Tong, and Min Wu (2020), Learning Causal Effect Using Machine Learning with Application to China's Typhoon. Acta Mathematicae Applicatae Sinica, English Series. 36(3): 702-713.

社会兼职

中国现场统计研究会因果推断分会理事，北京生物医学统计与数据管理研究会理事，ACM会员