I am always looking for highly self-motivated students to work with me as PhD, master or visiting students. Please drop me an email at firstname.lastname@example.org if you are interested in my research group.
Xu Chen is currently a tenure track associate professor at Gaoling School of Artificial Intelligence, Renmin University of China. Before that, he was a research fellow at University College London, UK, working with Prof. Jun Wang. He obtained his PhD degree from Tsinghua University, China, under the supervision of Prof. Zheng Qin. In the period from March to September of 2017, he was studying at Georgia Institute of Technology, USA, as a visiting scholar, supervised by Prof. Hongyuan Zha. His research aims to build explainable, fair and robust AI algorithms to understand human intellectual activities and decision making processes, especially under dynamic, heterogeneous and interactive environments. With this motivation, he is now focusing on the fields of recommendation system, LLM-based autonomous AI agents, causal inference and reinforcement learning.
- Workshop on Causality in Search and Recommendation (co-located with SIGIR 2021)
- Workshop on Machine Reasoning in Web Search and Data Mining (co-located with WSDM 2021)
- Workshop on ExplainAble Recommendation and Search (EARS 2020, co-located with SIGIR 2020)
- Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (co-located with WSDM 2018)
- ACM TORS SI on Causal Inference for Recommender Systems
- Frontiers in Big Data
- Tutorial on Explainable Recommendation and Search (SIGIR 2019)
- Background of Machine Learning (RLChina, http://rlchina.org/)
- DRL4IR: The 2nd Workshop on Deep Reinforcement Learning for Information Retrieval at SIGIR'21: Towards More Realistic User Long Term Engagement Modeling in Recommender Systems.
- CIPS tutorial: Pre-training enhanced Recommender Systems.
Area Chair: AACL-IJCNLP 2022
SPC: AAAI 2022, IJCAI 2021
PC: Recsys 2023, WSDM 2023-2024, KDD 2023, SIGIR Dataset track 2023, SIGIR 2022-2023, WWW 2021-2024, ICLR 2022-2024, ICML 2021-2023, NeurIPS 2021-2023, NeurIPS Dataset Track 2023, AAAI 2021, IJCAI 2023
Reviewer: ACM Transactions on Information Systems (TOIS),
IEEE Transactions on Knowledge and Data Engineering (TKDE),
ACM Transactions on Intelligent Systems and Technology (TIST),
Transactions on Machine Learning Research (TMLR),
Journal of Machine Learning Research (JMLR).
2023-9-22 Our explainable recommendation dataset "REASONER" got accepted by NeurIPS 2023 Dataset and Benchmarks Track.
2023-9-22 Papers on causal inference and reinforcement learning got accepted by NeurIPS 2023.
2023-9-19 We have released the second version of "RecAgent".
2023-9-8 We have released the second version of "A Survey on LLM-based Autonomous Agents".
2023-8-23 We have released a survey paper "A Survey on LLM-based Autonomous Agents". See Highlighted Research for more details.
2023-6-21 Papers on fairness aware recommendation got accepted by RecSys 2023.
2023-6-5 We have released the first version of "RecAgent", which explores the intersection of user behavior analysis and LLM-based autonomous agents. See Highlighted Research for more details.
2023-5-22 One paper on robust recommendation got accepted by KDD 2023.
2023-4-4 One paper on robust recommendation got accepted by SIGIR 2023.
2023-3-16 Give talks on "Recent advances in Explainable Recommendation" at MLNLP, University of Science and Technology of China (USTC) and BAAI.
2023-3-2 We have built a new explainable recommendation dataset REASONER.
2023-1-25 Papers on explainable and robust recommendation got accepted by TheWebConf 2023.
2023-1-15 Our paper on "RecBole" got CIKM 2022 best resource paper runner up award.
2023-1-7 One paper on debiased recommendation got accepted by TOIS 2023.
2022-9-10 Papers on explainable recommendation and ``RecBole`` got accepted by ICDE 2023 and CIKM 2022.
2022-7-7 One paper on reinforcement learning got accepted by Artificial Intelligence (AIJ) 2022.
2022-6-20 One paper on AI creation got accepted by MM 2022.
2022-6-5 Welcome to submit papers to ACM Transactions on Recommender Systems (TORS) Special Issue on Causal Inference for Recommender Systems.
2022-2-15 One survey paper on the evaluation of explainable recommendation was released.
2022-1-20 Papers on debiased and explainable recommendation got accepted by TheWebConf 2022.
2021-08-11 Our recommendation tool ``RecBole`` (https://recbole.io/) got accepted by CIKM 2021.
2021-08-11 Papers on explainable and causal recommendation got accepted by CIKM 2021.
2021-05-08 One paper on multi-agent evaluation and matrix completion got accepted by ICML 2021.
2021-04-15 One paper on causal recommendation got accepted by SIGIR 2021.
2021-01-16 Two papers on recommendation and reinforcement learning got accepted by TheWebConf 2021.
2020-12-20 Paper on multi-agent RL got accepted by AAMAS 2021.
2020-11-19 Join Gaoling School of Artificial Intelligence, Renmin University of China as an assistant professor.