I am a fourth-year Ph.D. candidate at Peking University, where I am fortunate to be advised by Prof. Xiao-Hua Zhou, coadvised by Prof. Zhi Geng and Prof. Peng Cui. Before that, I am honored to be selected into the 20th Experimental Class for Gifted Children in Beijing No.8 Middle School, which enables me to finish all grade 6-12 course works in 4 years and entering university at the age of 15. I have more than 40 publications appeared in several top conferences such as ICML, NeurIPS, ICLR, SIGKDD, WWW, SIGIR, AAAI, and IJCAI. My research interests span from causal machine learning theory, counterfactual fairness, recommender system debiasing, out-of-distribution generalization, multi-source data fusion, bioinformatics, and large language models. Moreover, I am supported by the Young Scientists Fund of the National Natural Science Foundation of China (¥300,000), and have served as the AC or SPC/PC-member for top-tier conferences including ICML, NeurIPS, ICLR, SIGKDD, WWW, AAAI, IJCAI, and the invited reviewer for prestigious journals such as TOIS, TPAMI, TKDE, TKDD, TNNLS, JASA, SCIENCE CHINA Information Sciences, and The Innovation.

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1. Our AAAI 2025 Workshop on Artificial Intelligence with Causal Techniques (AICT):
- Submission Deadline: Nov 24 2024 11:59PM UTC-0
- Submission Website

2. Our Special Issue of Entropy (JCR=2, CiteScore=4.9) on Causal Inference in Recommender Systems with Prof. Fuli Feng and Prof. Xu Chen:
- Submission Deadline: April 15 2025
- Submission Website

3. Hiring postdocs, PhD students, and research interns in causality and machine learning and information retrieval. Requirements:
- Strong code ability (Python or C/C++)
- Determination to do high-quality research or interested in practical applications
We provide competitive salary, sufficient funding, and good career opportunities.

Selected Publications

In the Year of 2025:

pdf	CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds Lei Wang, Jianxun Lian, Yi Huang, Yanqi Dai, Haoxuan Li, Xu Chen, Xing Xie and Ji-Rong Wen NAACL 2025 (Main Conference)

pdf	Label Correlation Biases Direct Time Series Forecast Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li* and Dacheng Tao* ICLR 2025 (Full, Accepted Rate: 32.08%)

pdf	Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang and Wenjing Yang ICLR 2025 (Full, Accepted Rate: 32.08%)

pdf	Optimal Transport for Time Series Imputation Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, Bin Chen and Zhichao Chen ICLR 2025 (Full, Accepted Rate: 32.08%)

pdf	CAP: Causal Air Quality Index Prediction Under Interference with Unmeasured Confounding Huayi Yang, Chunyuan Zheng, Guorui Liao, Shanshan Huang, Jun Liao, Zhili Gong, Haoxuan Li and Li Liu WWW 2025 (Full, Accept Rate: 20.0%)

pdf	Unifying Within and Across: Intra-Modality Multi-View Fusion and Inter-Modality Alignment for Knowledge Graph Completion Zhen Li, Jibin Wang, Zhuo Chen, Kun Wu, Meng Ai, Leike An, Liqiang Wang and Haoxuan Li* ICASSP 2025 (Full)    * Corresponding Author

pdf	Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity Recognition Haoyu Xie, Haoxuan Li, Chunyuan Zheng, Haonan Yuan, Guorui Liao, Jun Liao and Li Liu AAAI 2025 (Full, Accepted Rate: 4.63%)   (Oral)

pdf	HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units Guorui Liao, Chunyuan Zheng, Li Cheng, Haoyu Xie, Shanshan Huang, Jun Liao, Haoxuan Li and Li Liu AAAI 2025 (Full, Accepted Rate: 4.63%)   (Oral)

pdf	A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding Chuan Zhou, Yaxuan Li, Chunyuan Zheng, Haiteng Zhang, Min Zhang, Haoxuan Li* and Mingming Gong* KDD 2025 (Full, Accepted Rate: 19%)    * Corresponding Author

pdf	Classifying Treatment Responders: Bounds and Algorithms Anpeng Wu#, Haoxuan Li#, Chunyuan Zheng#, Kun Kuang and Kun Zhang KDD 2025 (Full, Accepted Rate: 19%)    # Equal Contribution

pdf	Entire Space Counterfactual Learning for Reliable Content Recommendations Hao Wang, Zhichao Chen, Zhaoran Liu, Haozhe Li, Degui Yang, Xinggao Liu, Haoxuan Li* IEEE Transactions on Information Forensics and Security (TIFS, CCF-A)    * Corresponding Author

In the Year of 2024:

pdf	A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs Haoxuan Li, Yue Liu, Zhi Geng and Kun Zhang NeurIPS 2024 (Full, Accepted Rate: 25.8%)

pdf	Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization Zhikang Chen, Min Zhang, Sen Cui, Haoxuan Li*, Gang Niu, Mingming Gong, Changshui Zhang and Kun Zhang NeurIPS 2024 (Full, Accepted Rate: 25.8%)    * Corresponding Author

pdf	Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation Yanghao Xiao, Haoxuan Li, Yongqiang Tang and Wensheng Zhang NeurIPS 2024 (Full, Accepted Rate: 25.8%)

pdf	Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song and Hao Wang NeurIPS 2024 (Full, Accepted Rate: 25.8%)

pdf	Towards Understanding Extrapolation: A Causal Lens Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing and Kun Zhang NeurIPS 2024 (Full, Accepted Rate: 25.8%)

pdf	Debiased Recommendation with Noisy Feedback Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng and Xiao-Hua Zhou KDD 2024 (Full, Accepted Rate: 20%)

pdf	Your Neighbor Matters: Towards Fair Decisions Under Networked Interference Wenjing Yang#, Haotian Wang#, Haoxuan Li#, Hao Zou, Ruochun Jin, Kun Kuang and Peng Cui KDD 2024 (Full, Accepted Rate: 20%)    # Equal Contribution

pdf	Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Hao Wang, Peng Wu, Zhi Geng, Xu Chen and Xiao-Hua Zhou ICML 2024 (Full, Accepted Rate: 3.6%)    (Spotlight)

pdf	On the Maximal Local Disparity of Fairness-Aware Classifiers Jinqiu Jin, Haoxuan Li* and Fuli Feng ICML 2024 (Full, Accepted Rate: 27.5%)    *Corresponding Author

pdf	Learning Causal Relations from Subsampled Time Series with Two Time-Slices Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang and Fei Wu ICML 2024 (Full, Accepted Rate: 3.6%)    (Spotlight)

pdf	A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Qingyu Cao and Kun Kuang ICML 2024 (Full, Accepted Rate: 27.5%)

pdf	Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu and Kun Kuang ICML 2024 (Full, Accepted Rate: 27.5%)

pdf	Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games Anjie Liu, Jianhong Wang, Haoxuan Li, Xu Chen, Jun Wang, Samuel Kaski and Mengyue Yang ICML 2024 Workshop Humans-Algs-Society

pdf	Debiased Collaborative Filtering with Kernel-Based Causal Balancing Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen and Peng Cui ICLR 2024 (Full, Accepted Rate: 5%)    (Spotlight)

pdf	Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng and Xiangnan He ICLR 2024 (Full, Accepted Rate: 31%)

pdf	MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation Min Zhang, Haoxuan Li, Fei Wu and Kun Kuang ICLR 2024 (Full, Accepted Rate: 31%)

pdf	Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu and Kun Kuang AAAI 2024 (Full, Accepted Rate: 23.75%)

pdf	Uncovering the Propensity Identification Problem in Debiased Recommendations Honglei Zhang, Shuyi Wang, Haoxuan Li, Chunyuan Zheng, Xu Chen, Li Liu, Shanshan Luo and Peng Wu ICDE 2024 (Full, Accepted Rate: 22.75%)

In the Year of 2023:

pdf	Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He and Peng Wu NeurIPS 2023 (Full, Accepted Rate: 26.1%)

pdf	Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach Jinqiu Jin#, Haoxuan Li#, Fuli Feng, Sihao Ding, Peng Wu and Xiangnan He NeurIPS 2023 (Full, Accepted Rate: 26.1%)    # Equal Contribution

pdf	Optimal Transport for Treatment Effect Estimation Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong and Ruiming Tang NeurIPS 2023 (Full, Accepted Rate: 26.1%)

pdf	CounterCLR: Counterfactual Contrastive Learning with Non-Random Missing Data in Recommendation Jun Wang, Haoxuan Li, Chi Zhang, Dongxu Liang, Enyun Yu, Wenwu Ou and Wenjia Wang ICDM 2023 (Short, Accpeted Rate: 19.9%)

pdf	Pareto Invariant Representation Learning for Multimedia Recommendation Shanshan Huang#, Haoxuan Li#, Qingsong Li, Chunyuan Zheng and Li Liu ACMMM 2023 (Full, Accept Rate: 29.3%)    # Equal Contribution

pdf	ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He and Xiao-Hua Zhou RecSys 2023 (Short, Accepted Rate: 25.3%)

pdf	Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu and Peng Cui KDD 2023 (Full, Accept Rate: 22.1%)

pdf	Propensity Matters: Measuring and Enhancing Balancing for Recommendation Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu and Peng Cui ICML 2023 (Full, Accept Rate: 27.9%)

pdf	Trustworthy Policy Learning under the Counterfactual No-Harm Criterion Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu and Peng Wu ICML 2023 (Full, Accept Rate: 27.9%)

pdf	Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations Haoxuan Li, Yanghao Xiao, Chunyuan Zheng and Peng Wu WWW 2023 (Full, Accept Rate: 19.2%)

pdf	TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations Haoxuan Li, Yan Lyu, Chunyuan Zheng and Peng Wu ICLR 2023 (Full, Accepted Rate: 31.8%)

pdf	StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random Haoxuan Li, Chunyuan Zheng and Peng Wu ICLR 2023 (Full, Accepted Rate: 31.8%)

pdf	Multiple Robust Learning for Recommendation Haoxuan Li#, Quanyu Dai#, Yuru Li, Yan Lyu, Zhenhua Dong, Xiao-Hua Zhou and Peng Wu AAAI 2023 (Full Oral, Accepted Rate: 10.8%)    # Equal Contribution

In the Year of 2022:

pdf	On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges Peng Wu#, Haoxuan Li#, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang and Xiao-Hua Zhou IJCAI 2022 (Survey Track, Accepted Rate: 18.0%)    # Equal Contribution

pdf	A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang and Jie Sun KDD 2022 (Full, Accepted rate: 14.9%)

Tutorials

pdf	ICDM 2024 Tutorial on Causality and Large Models Haoxuan Li, Chuan Zhou, Mengyue Yang, Mingming Gong, Jun Wang and Xiao-Hua Zhou ICDM 2024

pdf	ACML 2024 Tutorial on Causality and Large Models Haoxuan Li, Chuan Zhou, Mengyue Yang and Mingming Gong ACML 2024

pdf	DAI 2024 Tutorial on Causal Empowered Agents & Foundation Models Mengyue Yang and Haoxuan Li DAI 2024

pdf	SIGIR 2023 Tutorial on Causal Recommendation: Progresses and Future Directions Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng and Xiangnan He SIGIR 2023    Slides

Workshops

pdf	ICLR 2025 Workshop on World Models: Understanding, Modelling and Scaling Mengyue Yang, Haoxuan Li, Firas Laakom, Xidong Feng, Jiaxin Shi, Zhu Li, Francesco Faccio, Jürgen Schmidhuber ICLR 2025

pdf

AAAI 2025 Workshop on Artificial Intelligence with Causal Techniques Haoxuan Li (co-chair), Zhouchen Lin (co-chair), Yan Liu (co-chair), Xiao-Hua Zhou (co-chair), Yongqiang Chen, Mingming Gong, Amit Sharma, Hao Wang, Jun Wang, Mengyue Yang, Hanwang Zhang, Kun Zhang, Min Zhang and Chunyuan Zheng (alpha-beta order) AAAI 2025

pdf	NeurIPS 2024 Workshop on Causal Representation Learning Guangyi Chen, Haoxuan Li, Sara Magliacane, Zhijing Jin, Biwei Huang, Francesco Locatello, Peter Spirtes and Kun Zhang NeurIPS 2024    Website

pdf	NeurIPS 2024 Workshop on Causality and Large Models Felix Leeb, Ching Lam Choi, Luigi Gresele, Josef Valvoda, Andrei Liviu Nicolicioiu, Xiusi Li, Patrik Reizinger, Sophie Xhonneux, Haoxuan Li, Mengyue Yang, Bernhard Schölkopf and Dhanya Sridhar NeurIPS 2024    Website

pdf	ICDM 2024 Workshop on Causal Representation Learning Mingming Gong, Guangyi Chen, Haoxuan Li, Mengyue Yang, Defu Cao, Xiangchen Song, Bo Han and Tongliang Liu ICDM 2024    Website

Patents

pdf	基于非随机缺失数据处理结局测量误差的推荐方法和系统 Xiao-Hua Zhou, Haoxuan Li and Chunyuan Zheng Patent Number: ZL 2023 1 1815813.1

pdf	一种推荐系统预测模型的训练方法 Xiao-Hua Zhou, Haoxuan Li and Chunyuan Zheng Patent Number: ZL 2023 1 1812694.4

pdf	一种基于缺失数据填补的推荐方法和系统 Xiao-Hua Zhou, Haoxuan Li and Chunyuan Zheng Patent Number: ZL 2023 1 1206930.8

pdf	一种结合非临床数据的药物不良反应预测方法和系统 Xiao-Hua Zhou, Haoxuan Li and Taojun Hu Patent Number: ZL 2023 1 0530341.9

pdf	一种癫痫分类方法和系统 Xiao-Hua Zhou, Xiaoxin Liu, Haoxuan Li, Taoyun Ji and Tong Lin Patent Number: ZL 2023 1 1557824.4

pdf	一种满足反事实无害标准的可信策略学习方法及装置 Yue Liu, Chunyuan Zheng, Haoxuan Li, Peng Wu, Yixiao Cao and Zhi Geng Patent Number: ZL 2023 1 0916949.5

Selected Awards

National Scholarship (国家奖学金),    2024    - Ministry of Education, China

Outstanding Merit Student (北京大学三好学生标兵),    2024    - Peking University

Peking University President Scholarship (北京大学校长奖学金),    2023    - Peking University

Merit Student (北京大学三好学生),    2023    - Peking University

UBIQUANT Scholarship (九坤奖学金),    2023    - Peking University

Peking University President Scholarship (北京大学校长奖学金),    2022    - Peking University

Top Award (北京大学第三十一届“挑战杯”特等奖),    2022    - "Challenge Cup" at Peking University

Best Poster Award (北京大学第三十一届“挑战杯”最佳海报奖),    2022    - "Challenge Cup" at Peking University

National Scholarship (国家奖学金),    2021    - Ministry of Education, China

Invited Talk

Department of Computer Science and Technology, Tsinghua University. Invited by Dr. Peng Cui, Causal Inference and Data Mining in Complex Scenarios. Jun 2023

Gaoling School of Artificial Intelligence, Renmin University of China. Invited by Dr. Xu Chen, Towards Causal Recommender Systems. Mar 2023

College of Computer Science and Technology, Zhejiang University. Invited by Dr. Kun Kuang, Causal Inference and Data Mining in Complex Scenarios. Mar 2023

School of Computer Science and Information Engineering, Hefei University of Technology. Invited by Dr. Le Wu, Towards Causal Recommender Systems. Mar 2023

School of Data Science, University of Science and Technology of China. Invited by Dr. Fuli Feng, Towards Causal Recommender Systems. Mar 2023

Youth PhD Talk, Gou'xiong'hui. Invited by Ying Chang, Causal Inference for Data Mining: Framework, Methods and Theory. Mar 2023

CAS and PolyU SIAM Student Chapters Joint Workshop 2022. Invited by Dr. Xiaojun Chen, Causal Machine Learning and its Application in Recommender Systems. Dec 2022

School of Mathematics and Statistics, Beijing Technology and Business University. Invited by Dr. Zhi Geng, Causal Recommender Systems: Formalization and Debiasing. Nov 2022

Data mining and Information Retrieval Laboratory (DMIR), Guangdong University of Technology. Invited by Dr. Ruichu Cai, Recent Advances in Causal Recommender Systems. Sep 2022

SIGMA: Special Interest Group on Mathematics, Algorithm, Institute of Computing Technology, Chinese Academy of Sciences. Invited by Dr. Qing He, Causal Inference with Deep Learning, and Applications in Recommender Systems. Sep 2022

Swarma-Kaifeng Scholar Seminar, Causality and Complex Systems, in Hangzhou, China. Invited by Dr. Jiang Zhang, Causal-inspired Reinforcement Learning Off-Policy Strategies: Evaluation and Learning. Aug 2022

Professional Services

Program Committee Member of ICML Program Committee Member of NeurIPS Program Committee Member of ICLR Program Committee Member of KDD Program Committee Member of WWW Program Committee Member of ACMMM Invited Reviewer for Journal of the American Statistical Association (JASA) Invited Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE) Invited Reviewer for ACM Transactions on Information Systems (TOIS) Invited Reviewer for IEEE Transactions on Neural Networks and Learning Systems (TNNLS) Invited Reviewer for ACM Transactions on Recommender Systems (TORS) Invited Reviewer for IEEE Transactions on Circuits and Systems for Video Technologys (TCSVT) Invited Reviewer for The Innovation Invited Reviewer for SCIENCE CHINA Information Sciences

Last update: 17 September, 2024. Webpage template borrows from Weinan Zhang.