• Shi Yansong

    Assistant Professor

    Information Management and Business Intelligence (IM&BI)

    Add: Guoshun Road Siyuan Building Room 411, Siyuan Building

    Tel: 25011053(TEL)

    E-mail: shiys@fudan.edu.cn

    Research Field: Machine Learning, Causal Inference, Consumer Behavioral Bias, Reinforcement Learning, Data Mining

    Website:

    Teacher information
    Achievements in scientific research
    Academic activities and community service

    Educational Background

    Doctor Degree,Management Science & Engineering,Tsinghua University

    Bachelor Degree,Information Management & Information Systems,Beihang University

    Awards on Research

    2025.10,Best Paper Award, The Fifth Annual Conference of the Institute of Artifical Intelligence for Management,Society of Management Science and Engineering of China

    2024.10,Innovative Scientific Research Achievement Award of China Information Economics in 2024,China Information Economics Society

    2022.12,Best Paper Nomination,The Tenth CNAIS National Congress

    2021.12,ICIS 2021 Best Kauffman Student Paper Award,Association for Information Systems


    Journal Papers


    1.Cong Wang, Yansong Shi, Xunhua Guo, and Guoqing Chen2025Probing digital footprints and reaching for inherent preferences: A cause-disentanglement approach to personalized recommendationsInformation Systems Research forthcoming 1314-1332.  


    Conference Proceedings


    1.Tianyu Zhu, Yansong Shi, Yuan Zhang, Yihong Wu, Fengran Mo, and Jian-Yun Nie2024Collaboration and transition: distilling item transitions into multi-query self-attention for sequential recommendationWSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data Mining Merida, Mexico 1003-1011.  



    2.Yansong Shi, Cong Wang, Xunhua Guo, and Guoqing Chen2022Personalized recommendation through disentangled representation learning of consumers’ multiple digital footprintsICIS 2022 Proceedings 8 1-18.  



    3.Yansong Shi, Cong Wang, Xunhua Guo, and Guoqing Chen2021Training personalized recommender systems with biased data: A joint likelihood approach to modeling consumer self-selection behaviorsICIS 2021 Proceedings 11 1-18.  


    Research Projects

    2026.01—2030.12MemberResearch on Service Innovation and Service Quality Evaluation Driven by Artificial Intelligence Technologies for Smart, Connected ProductsNational Natural Science Foundation of China

    2026.01—2028.12Principal InvestigatorPrincipal Investigator, Research on Causal Recommendation Approach for Mitigating Consumer Behavior Data BiasesNational Natural Science Foundation of China