I received my Ph.D. degree in computer science and technology from Beijing Jiaotong University in 2024, supervised by Professor Prof. Jun Wu. I received my B.S. degree in electronic information science and technology from Hefei University of Technology in 2018.

My research interests are machine learning and data mining for the applications of recommender systems. My recent working topics include but are not limited to:

• Learning to Hash for recommender systems

• Learning to Rank for recommender systems

• Learning to Debias for recommender systems

📑Publications

• [PR2025] Fangyuan Luo, Yankai Chen, Jun Wu, Yidong Li. Rank Gap Sensitive Deep AUC Maximization for CTR Prediction. Pattern Recognition, 2025. (SCI Q1, CCF-B Journal) [paper] [codes] [slides] [poster]

• [AAAI 2024] Fangyuan Luo, Jun Wu. Optimizing Recall in Deep Graph Hashing Framework for Item Retrieval (Student Abstract). The 38th AAAI Conference on Artificial Intelligence, 2024. (CCF-A Conference) [paper] [codes] [slides] [poster]

• [ACM TKDD 2024] Fangyuan Luo, Jun Wu, Tao Wang. Discrete Listwise Content-Aware Recommendation. ACM Transactions on Knowledge Discovery from Data, 2023. (CCF-B Journal) [paper] [codes] [slides] [poster]

• [SIGIR 2023] Fangyuan Luo, Jun Wu. User-Dependent Learning to Debias for Recommendation. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023. (CCF-A Conference) [paper] [codes] [slides] [poster]

• [ACM TOIS 2023] Honglei Zhang, Fangyuan Luo, Jun Wu, Xiangnan He, Yidong Li. LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization. ACM Transactions on Information Systems, 2023. (CCF-A Journal) [paper] [codes] [slides] [poster]

• [IJCAI 2022] Fangyuan Luo, Jun Wu, Tao Wang. Discrete Listwise Personalized Ranking for Fast Top-N Recommendation with Implicit Feedback. The International Joint Conferences on Artificial Intelligence (IJCAI), 2022. (CCF-A Conference) [paper] [codes] [slides] [poster]

• [SIGIR 2022] Shuang Tang, Fangyuan Luo, Jun Wu. Smooth-AUC: Smoothing the Path Towards Rank-based CTR Prediction. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022. (CCF-A Conference) [paper] [codes] [slides] [poster]

• [AAAI 2021] Fangyuan Luo, Jun Wu, Haishuai Wang. Semi-Discrete Social Recommendation (Student Abstract). The 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (CCF-A Conference) [paper] [codes] [slides] [poster]

• [DASFAA 2021] Junheng Huang, Fangyuan Luo, Jun Wu. Semi-supervised Factorization Machines for Review-Aware Recommendation. The 26th International Conference on Database Systems for Advanced Applications (DASFAA), 2021. (CCF-B Conference) [paper] [codes] [slides] [poster]

• [IEEE IS 2020] Jun Wu, Fangyuan Luo, Yujia Zhang, Haishuai Wang. Semi-discrete Matrix Factorization. IEEE Intelligent Systems, 2020. (The organizer of AI's 10 to Watch) [paper] [codes] [slides] [poster]

🏆Services & Awards

Services

Journal Reviewer

• Transactions on Information Systems (TOIS)
• Transactions on Knowledge and Data Engineering (TKDE)
• Transactions on Knowledge Discovery from Data (TKDD)
• Knowledge and Information Systems (KIS)
• The Journal of Supercomputing
• Cluster Computing-The Journal of Networks Software Tools and Applications

PC Member

• The 30th International Conference on Database Systems for Advanced Applications (DASFAA 2025)
• AAAI 2026

Awards

• SIGIR Student Travel Award (2022)

🧑‍🏫Teaching