Short Bio

Jun Xu is a Professor at Gaoling School of Artificial Intelligence, Renmin University of China. He received his B.E. and Ph.D. in Computer Science from Nankai University, in 2001 and 2006, respectively. He worked as an associate researcher, researcher, and professor at Microsoft Research Asia, Huawei Noah’s Ark Lab, and Institute of Computing Technology, Chinese Academy of Sciences. He joined Renmin University of China in Sep. 2018. His research interests focus on applying machine learning to information retrieval and recommendation. He has published more than 80 papers and 2 monographs at top international journals and conferences, including TKDE, TOIS, JMLR, FnTIR, SIGIR, CIKM, ACL, EMNLP etc. His work on information retrieval has received the Test of Time Award Honorable mention of ACM SIGIR 2019, Best Paper Runner-up of ACM CIKM 2017, and Best Paper Award of AIRS 2010. He has served or is serving top international conferences as Senior PC members, including SIGIR, ACML, CIKM, AAAI, and top international journal of JASIST as an editorial board member, and ACM TIST as an associate editor. He has given tutorials at top conferences like SIGIR, WSDM, TheWebConf (WWW) on the topic of deep learning for semantic matching in search and recommendation.

Education

• Ph. D. in Computer Science, College of Information Science and Technology, Nankai University Tianjin, China, 2001 - 2006
• B. S. in Computer Science, College of Information Science and Technology, Nankai University Tianjin, China, 1997 - 2001

Work Experience

• Professor, School of Information, Renmin University of China Beijing, China, 2018 -
• Researcher & Professor, Institute of Computing Technology, Chinese Academy of Sciences Beijing, China, 2014 - 2018
• Researcher and Senior Researcher, Noah’s Ark Lab, Huawei Technologies Hong Kong SAR, China, 2012 - 2014
• Associate Researcher, Microsoft Research Asia (MSRA) Beijing, China, 2006 – 2012

Research Interests

His research interests span the areas of intelligent information retrieval, recommender systems, and big data analysis. He has specific interests in reinforcement learning to rank, deep learning for semantic matching and relevance ranking, and casual inference in IR.

Selected Publications

Book

Jun Xu, Xiangnan He and Hang Li. “Deep Learning for Matching in Search and Recommendation”, Now Publishers, 2020. (pdf, link)

Hang Li and Jun Xu. “Semantic Matching in Search”, Now Publishers, 2014. (pdf, link)

Paper

2023:

Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen. Reward Imputation with Sketching for Contextual Batched Bandits. NeurIPS 2023. [PDF]

Zhongxiang Sun, Weijie Yu, Zihua Si, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen. Explainable Legal Case Matching via Graph Optimal Transport. TKDE. [PDF]

Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, Yuan Wang, Quan Lin, and Jun Xu. Reinforcement Re-ranking with 2D Grid-based Recommendation Panels. SIGIR-AP 23. [PDF]

Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen. Unbiased Top-$k$ Learning to Rank with Causal Likelihood Decomposition. SIGIR-AP 23. [PDF]

Chenglei Shen, Xiao Zhang, Wei Wei, Jun Xu. HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendation. CIKM 2023. [PDF]

Zhongxiang Sun, Zihua Si, Xiaoxue Zang, Dewei Leng, Yanan Niu, Yang Song, Xiao Zhang, Jun Xu. KuaiSAR: A Unified Search And Recommendation Dataset. CIKM 2023. [PDF]

Sunhao Dai, Yuqi Zhou, Jun Xu, Ji-Rong Wen. Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction. CIKM 2023. [PDF]

Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu. Uncovering ChatGPT’s Capabilities in Recommender Systems. RecSys 2023. [PDF]

Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong, Wen. Syntactic-Informed Graph Networks for Sentence Matching. TOIS. [PDF]

Haiyuan Zhao, Lei Zhang, Jun Xu, Guohao Cai, Zhenhua Dong and Ji-Rong Wen. Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation. RecSys 2023. [PDF]

Sirui Chen, Yuan Wang, Zijing Wen, Zhiyu Li, ChangShuo Zhang, Xiao Zhang, Lin Quan, Cheng Zhu, Jun Xu. Controllable Multi-Objective Re-ranking with Policy Hypernetworks. KDD 2023 (ADS track). [PDF]

Ruiqi Zhao, Lei Zhang, Shengyu Zhu, Zitong Lu, Zhenhua Dong, Chaoliang Zhang, Jun Xu, Zhi Geng, Yangbo He. Conditional Counterfactual Causal Effect for Individual Attribution. UAI 2023. [PDF]

薄琳，庞亮，张朝亮，王钊伟，董振华，徐君，文继荣. ACRank: 在神经排序模型中引入检索公理知识. 计算机学报. [PDF]

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai and Ji-Rong Wen. When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation. SIGIR 2023. [PDF]

Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen. Law Article-Enhanced Legal Case Matching: a Causal Learning Approach. SIGIR 2023. [PDF]

张乐凭，徐君，庞亮，董振华，文继荣. U-SetRank：基于注意力机制修正的SetRank纠偏. 计算机研究与发展. [PDF]

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Yang Song, Xiaoxue Zang, Ji-Rong Wen. Enhancing Recommendation with Search Data in a Causal Learning Manner. TOIS vol.41. [PDF]

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System. WWW 2023 (Splotlight - Best Paper Nomination). [PDF]

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System. WWW 2023. [PDF]

2022:

Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen. Counteracting user attention bias in music streaming recommendation via reward modification. KDD 2022. [PDF]

Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen. Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction. SIGIR 2022. [PDF]

Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang Song, Ji-Rong Wen. A Model-Agnostic Causal Learning Framework for Recommendation using Search Data. WWW 2022. [PDF]

Weijie Yu; Chen Xu; Jun Xu; Liang Pang; Ji-Rong Wen. Distribution Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains. TASLP vol.30. [PDF]

Weijie Yu, Liang Pang, Jun Xu, Bing Su, Zhenhua Dong, Ji-Rong Wen. Optimal Partial Transport Based Sentence Selection for Long-form Document Matching. COLING 2022. [PDF]

Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong Wen. Semantic Sentence Matching via Interacting Syntax Graphs. COLING 2022. [PDF]

Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, Ji-Rong Wen. Dually Enhanced Propensity Score Estimation in Sequential Recommendation. CIKM 2022. [PDF]

Kerui Xu, Jun Xu, Sheng Gao, Si Li, Jun Guo, Ji-Rong Wen. A Tag-Based Post-Hoc Framework for Explainable Conversational Recommendation. ICTIR 2022. [PDF]

Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenghua Dong, Ji-rong Wen. Separating Examination and Trust Bias from Click Predictions for Unbiased Relevance Ranking. WSDM 2023. [PDF]

Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang,Xiaohui Yan. Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient. ICTIR 2022. [PDF]

2021:

Xiao Zhang, Shizhong Liao, Jun Xu, Ji-Rong Wen. Regret Bounds for Online Kernel Selection in Continuous Kernel Space. AAAI 2021. [PDF]

Xiao Zhang, Haonan Jia, Hanjing Su, Wenhan Wang, Jun Xu, Ji-Rong Wen. Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback. SIGIR 2021. [PDF]

Kerui Xu, Jingxuan Yang, Jun Xu, Sheng Gao, Jun Guo, Ji-Rong Wen. Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation. WSDM 2021. [PDF]

Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Nianwen Xue, Ji-Rong Wen. A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech. ACL 2021. [PDF]

Jing Yao, Zhicheng Dou, Jun Xu, Ji-Rong Wen. RLPS: A reinforcement learning–based framework for personalized search. TOIS 2021. [PDF]