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教师

Faculty
教师 Faculty
黎波

管理科学与工程系    长聘副教授

电话：(86)(10)62795143

办公室：李华楼B421

邮箱：libo@sem.tsinghua.edu.cn

开放时间：邮件预约

教育经历

2002年 北京大学 数学学士

2006年 加州大学伯克利分校 统计学博士

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工作经历

2006 至今，先后担任清华大学经济管理学院 助理教授、副教授、长聘副教授，主持国家自然科学基金青年项目、面上项目，北京市青年英才计划项目，清华大学自主科研项目，及腾讯、字节跳动等公司合作项目。曾获得第四届清华大学“清韵烛光”我最喜爱的教师称号。


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讲授课程

概率论与数理统计、高等数理统计、大数据分析

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研究领域

复杂数据驱动的决策与预测、人工智能与经济社会

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学术成果

谷歌学术主页

https://scholar.google.com/citations?hl=zh-CN&user=GaJXFWMAAAAJ


  1. Wang, Kang, Xu, Renzhe, Li, Bo. (2026). Lower Bias, Higher Welfare: How Creator Competition Reshapes Bias-Variance Tradeoff in Recommendation Platforms? KDD 2026.

  2. Shi, Bowen, Mao, Xiaojie, Yang, Mochen, Li, Bo. (2025). What, Why, and How: An Empiricist’s Guide to Double/Debiased Machine Learning. Information Systems Research, forthcoming.

  3. Xu, Renzhe, Wang, Haotian, Zhang, Xingxuan, Li, Bo, Cui, Peng. (2025). Ppa-game: Characterizing and learning competitive dynamics among online content creators. KDD 2025.

  4. Xu, Renzhe, Wang, Kang, Li, Bo. (2025). Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. ICML 2025.

  5. Chhabra, Anshuman, Li, Bo, Chen, Jian, Mohapatra, Prasant, Liu, Hongfu. (2025). Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models. ICML 2025 (Oral).

  6. Zhu, Minqin, Wu, Anpeng, Li, Haoxuan, Xiong, Ruoxuan, Li, Bo, Wu, Fei, Kuang, Kun. (2025). Learning double balancing representation for heterogeneous dose-response curve estimation. Neural Networks, 107600.

  7. Zhao, Ziyu, Wu, Anpeng, Kuang, Kun, Xiong, Ruoxuan, Li, Bo, Wang, Zhihua, Wu, Fei. (2025). Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. IEEE Transactions on Knowledge and Data Engineering (TDKE), 32(2), 823-836.

  8. Liu, Jiashuo, Wu, Jiayun, Wang, Tianyu, Zou, Hao, Li, Bo, Cui, Peng. (2024). Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. ICML 2024.

  9. Zhu, Minqin, Wu, Anpeng, Li, Haoxuan, Xiong, Ruoxuan, Li, Bo, Yang, Xiaoqing, Qin, Xuan, Zhen, Peng, Guo, Jiecheng, Wu, Fei. (2024). Contrastive balancing representation learning for heterogeneous dose-response curves estimation. AAAI 2024.

  10. Liu, Jiashuo, Wu, Jiayun, Peng, Jie, Wu, Xiaoyu, Zheng, Yang, Li, Bo, Cui, Peng. (2024). Enhancing Distributional Stability among Sub-populations. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTAT) 2024.

  11. Zhao, Ziyu, Kuang, Kun, Li, Bo, Cui, Peng, Wu, Runze, Xiao, Jun, Wu, Fei. (2023). Differentiated matching for individual and average treatment effect estimation. Data Mining and Knowledge Discovery, 37(1), 205-227.

  12. Kuang, Kun, Wang, Haotian, Liu, Yue, Xiong, Ruoxuan, Wu, Runze, Lu, Weiming, Zhuang, Yueting, Wu, Fei, Cui, Peng, Li, Bo. (2023). Stable prediction with leveraging seed variable. IEEE Transactions on Knowledge and Data Engineering (TDKE), 35(6), 6392-6404.

  13. Wu, Anpeng, Yuan, Junkun, Kuang, Kun, Li, Bo, Wu, Runze, Zhu, Qiang, Zhuang, Yueting, Wu, Fei. (2023). Learning decomposed representations for treatment effect estimation. IEEE Transactions on Knowledge and Data Engineering (TDKE), 35(5), 4989-5001.

  14. Liu, Jiashuo, Shen, Zheyan, Cui, Peng, Zhou, Linjun, Kuang, Kun, Li, Bo. (2023). Distributionally robust learning with stable adversarial training. IEEE Transactions on Knowledge and Data Engineering (TDKE), 35(11), 11288-11300.

  15. Chen, Qianyi, Li, Bo, Deng, Lu, Wang, Yong. (2023). Optimized covariance design for ab test on social network under interference. NeurIPS 2023.

  16. Wu, Anpeng, Kuang, Kun, Xiong, Ruoxuan, Li, Bo, Wu, Fei. (2023). Stable estimation of heterogeneous treatment effects. ICML 2023.

  17. Xu, Renzhe, Wang, Haotian, Zhang, Xingxuan, Li, Bo, Cui, Peng. (2023). Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. ICML 2023.

  18. Wu, Anpeng, Kuang, Kun, Xiong, Ruoxuan, Zhu, Minqin, Liu, Yuxuan, Li, Bo, Liu, Furui, Wang, Zhihua, Wu, Fei. (2023). Learning instrumental variable from data fusion for treatment effect estimation. AAAI 2023.

  19. Liu, Jiashuo, Wu, Jiayun, Pi, Renjie, Xu, Renzhe, Zhang, Xingxuan, Li, Bo, Cui, Peng. (2023). Measure the predictive heterogeneity.  ICLR 2023.

  20. Zou, Hao, Wang, Haotian, Xu, Renzhe, Li, Bo, Pei, Jian, Jian, Ye Jun, Cui, Peng. (2023). Factual observation based heterogeneity learning for counterfactual prediction. Conference on Causal Learning and Reasoning 2023.

  21. Kuang, Kun, Cui, Peng, Zou, Hao, Li, Bo, Tao, Jianrong, Wu, Fei, Yang, Shiqiang. (2022). Data-driven Variable Decomposition for Treatment Effect Estimation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(5), 2120–2134.

  22. Yuan, Junkun, Wu, Anpeng, Kuang, Kun, Li, Bo, Wu, Runze, Wu, Fei, Lin, Lanfen. (2022). Auto IV: Counterfactual prediction via automatic instrumental variable decomposition. ACM Transactions on Knowledge Discovery from Data (TKDD), 16(4), 1-20.

  23. Xu, Renzhe, Zhang, Xingxuan, Li, Bo, Zhang, Yafeng, Chen, Xiaolong, Cui, Peng. (2022). Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS 2022.

  24. Liu, Jiashuo, Wu, Jiayun, Li, Bo, Cui, Peng. (2022). Distributionally Robust Optimization with Data Geometry. NeurIPS 2022.

  25. Zou, Hao, Li, Bo, Han, Jiangang, Chen, Shuiping, Ding, Xuetao, Cui, Peng. (2022). Counterfactual prediction for outcome-oriented treatments. ICML 2022.

  26. Wu, Anpeng, Kuang, Kun, Li, Bo, Wu, Fei. (2022). Instrumental variable regression with confounder balancing. ICML 2022.

  27. Xu, Renzhe, Zhang, Xingxuan, Li, Bo, Zhang, Yafeng, Chen, Xiaolong, Cui, Peng. (2022). Regulatory instruments for fair personalized pricing. WWW 2022.

  28. Kuang, Kun, Li, Yunzhe, Li, Bo, Cui, Peng, Yang, Hongxia, Tao, Jianrong, Wu, Fei. (2021). Continuous treatment effect estimation via generative adversarial de-confounding. Data Mining and Knowledge Discovery, 35(6), 2467-2497.

  29. Liu, Jiashuo, Hu, Zheyuan, Cui, Peng, Li, Bo, Shen, Zheyan. (2021). Kernelized Heterogeneous Risk Minimization. NeurIPS 2021.

  30. Liu, Jiashuo, Hu, Zheyuan, Cui, Peng, Li, Bo, Shen, Zheyan. (2021). Heterogeneous risk minimization. ICML 2021 (Spotlight).

  31. Liu, Jiashuo, Shen, Zheyan, Cui, Peng, Zhou, Linjun, Kuang, Kun, Li, Bo, Lin, Yishi. (2021). Stable adversarial learning under distributional shifts. AAAI 2021.

  32. Gu, Xinyue, Li, Bo. (2020). Cross-estimation for decision selection. Applied Stochastic Models in Business and Industry, 36(5), 932-958.

  33. Zou, Hao, Cui, Peng, Li, Bo, Shen, Zheyan, Ma, Jianxin, Yang, Hongxia, He, Yue. (2020). Counterfactual Prediction for Bundle Treatment. NeurIPS 2020.

  34. Xu, Renzhe, Cui, Peng, Kuang, Kun, Li, Bo, Zhou, Linjun, Shen, Zheyan, Cui, Wei. (2020). Algorithmic decision making with conditional fairness. KDD 2020.

  35. Shen, Zheyan, Cui, Peng, Liu, Jiashuo, Zhang, Tong, Li, Bo, Chen, Zhitang. (2020). Stable learning via differentiated variable decorrelation. KDD 2020.

  36. Kuang, Kun, Xiong, Ruoxuan, Cui, Peng, Athey, Susan, Li, Bo. (2020). Stable prediction with model misspecification and agnostic distribution shift. AAAI 2020.

  37. Kuang, Kun, Cui, Peng, Li, Bo, Jiang, Meng, Wang, Yashen, Wu, Fei, Yang, Shiqiang. (2019). Treatment effect estimation via differentiated confounder balancing and regression. ACM Transactions on Knowledge Discovery from Data (TKDD), 14(1), 1-25.

  38. Li, Bo, Liang, Baosheng, Tong, Xingwei, Sun, Jianguo. (2019). On estimation of partially linear varying-coefficient transformation models with censored data. Statistica Sinica, 29(4), 1963-1975.

  39. Wang, Hao, Li, Bo, Tong, Seung Hoon, Chang, In-Kap, Wang, Kaibo. (2018). A discrete spatial model for wafer yield prediction. Quality Engineering, 30(2), 169-182.

  40. Kuang, Kun, Cui, Peng, Athey, Susan, Xiong, Ruoxuan, Li, Bo. (2018). Stable prediction across unknown environments. KDD 2018.

  41. Shen, Zheyan, Cui, Peng, Kuang, Kun, Li, Bo, Chen, Peixuan. (2018). Causally regularized learning with agnostic data selection bias. ACM MM 2018.

  42. Kuang, Kun, Cui, Peng, Li, Bo, Jiang, Meng, Yang, Shiqiang. (2017). Estimating treatment effect in the wild via differentiated confounder balancing. KDD 2017.

  43. Kuang, Kun, Cui, Peng, Li, Bo, Jiang, Meng, Yang, Shiqiang, Wang, Fei. (2017). Treatment effect estimation with data-driven variable decomposition. AAAI 2017.

  44. He, Luo, Xie, Xiaolei, Liu, Hongyan, Li, Bo. (2017). How out-of-pocket ratio influences readmission: An analysis based on front sheet of inpatient medical record. International Conference on Smart Health, 67-78.

  45. Wang, Kaibo, Jiang, Wei, Li, Bo. (2016). A spatial variable selection method for monitoring product surface. International Journal of Production Research, 54(14), 4161-4181.

  46. Tao, Jialing, Wang, Kaibo, Li, Bo, Liu, Liang, Cai, Qi. (2016). Hierarchical models for the spatial-temporal carbon nanotube height variations. International Journal of Production Research, 54(21), 6613-6632.

  47. Liu, Angela, Mazumdar, Tridib, Li, Bo. (2015). Counterfactual decomposition of movie star effects with star selection. Management Science, 61(7), 1704-1721.

  48. Li, Bo, Wang, Chi, Wei, Li, Bo. (2014). Trends in China’s gender employment and pay gap: Estimating gender pay gaps with employment selection. Journal of Comparative Economics, 42(3), 708-725.

  49. Wang, Kaibo, Yeh, Arthur B, Li, Bo. (2014). Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation. Computational Statistics & Data Analysis, 78, 206-217.

  50. Li, Bo, Wang, Kaibo, Yeh, Arthur B. (2013). Monitoring the covariance matrix via penalized likelihood estimation. IIE Transactions, 45(2), 132-146.

  51. Yeh, Arthur B, Li, Bo, Wang, Kaibo. (2012). Monitoring multivariate process variability with individual observations via penalised likelihood estimation. International Journal of Production Research, 50(22), 6624-6638.

  52. Chi, Wei, Li, Bo, Yu, Qiumei. (2011). Decomposition of the increase in earnings inequality in urban China: A distributional approach. China Economic Review, 22(3), 299-312.

  53. Leng, Chenlei, Li, Bo. (2011). Forward adaptive banding for estimating large covariance matrices. Biometrika, 98(4), 821-830.

  54. Leng, Chenlei, Li, Bo. (2010). Least squares approximation with a diverging number of parameters. Statistics & Probability Letters, 80(3-4), 254-261.

  55. Li, Bo. (2009). Asymptotically distribution-free goodness-of-fit testing: A unifying view. Econometric Reviews, 28(6), 632-657.

  56. Wang, Hansheng, Li, Bo, Leng, Chenlei. (2009). Shrinkage tuning parameter selection with a diverging number of parameters. Journal of the Royal Statistical Society Series B: Statistical Methodology, 71(3), 671-683.

  57. Chi, Wei, Li, Bo. (2008). Glass ceiling or sticky floor? Examining the gender earnings differential across the earnings distribution in urban China, 1987-2004. Journal of Comparative Economics, 36(2), 243-263.

  58. Li, Bo. (2008). Nonparametric testing of an exclusion restriction in quantile regression. Communications in Statistics—Theory and Methods, 37(18), 2877-2889.

  59. Bickel, Peter, Li, Bo, Bengtsson, Thomas. (2008). Sharp failure rates for the bootstrap particle filter in high dimensions. In Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh (Vol. 3, pp. 318-330). Institute of Mathematical Statistics Collections.

  60. Bengtsson, Thomas, Bickel, Peter, Li, Bo. (2008). Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems. In Probability and Statistics: Essays in Honor of David A. Freedman (Vol. 2, pp. 316-335). Institute of Mathematical Statistics Collections.

  61. Bickel, Peter J, Li, Bo. (2007). Local polynomial regression on unknown manifolds. Institute of Mathematical Statistics Lecture Notes-Monograph Series, 177-186.

  62. Bickel, Peter J, Li, Bo. (2006). Regularization in statistics (with discussion and rejoinder). Test, 15(2), 303-344.

  63.  陆瑶，张叶青，黎波，赵浩宇. (2021). 高管个人特征与公司业绩 —— 基于机器学习的经验证据. 管理科学学报, 23(2), 120-140.

  64. 张晶，黄京华，黎波，严威. (2014). 新浪企业微博口碑传播的实证研究. 清华大学学报：自然科学版, 54(5), 649-654.

  65. 张露，黄京华，黎波. (2013). ERP 实施对企业绩效影响的实证研究 —— 基于倾向得分匹配法. 清华大学学报：自然科学版, (1), 117-121.

  66. 钱晓烨，迟巍，黎波. (2010). 人力资本对我国区域创新及经济增长的影响 —— 基于空间计量的实证研究. 数量经济技术经济研究, (4), 107-121.

  67. 迟巍，黎波，余秋梅. (2008). 基于收入分布的收入差距扩大成因的分解. 数量经济技术经济研究, 25(9), 52-64.

  68. 黎波，迟巍，余秋梅. (2007). 一种新的收入差距研究的计量方法 —— 基于分布函数的半参数化估计. 数量经济技术经济研究, 24(8), 119-129.


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