教授/研究员

刘思源

职称:教授、博导

所在系:决策科学系

  • 个人简介

    刘思源,华南理工大学工商管理学院与未来技术学院的双聘长聘正教授,同时担任华南理工大学商业科技研究中心主任及广东省智能认知与行为决策工程技术研究中心执行主任,并是教育部哲学社会科学创新团队核心成员。曾任美国宾夕法尼亚州立大学终身教授及冠名教授,长期致力于管理科学、数据科学与人工智能的交叉研究。在国际期刊和会议发表一系列学科交叉的研究论文,涵盖Management Science、Information Systems Research、INFORMS Journal on Computing、Production and Operations Management、Nature Communications、IEEE Transactions on Knowledge and Data Engineering、SIGKDD、SIGMOD、AAAI等。荣获多个学科交叉的学术奖励,如Management Science Best Paper Award in Information Systems (Finalist)、INFORMS Workshop on Data Science Best Paper Award、CPIC Research Achievement Award、Google Internet of Things Technology Research Award、Marketing Science Institute Award、Google Faculty Research Award、USDOT National University Transportation Center for Safety Award、Champion of Competition of High Performance Computing (Microsoft)、First Prize of High Performance Computing Scholar Program (Microsoft)等。政策报告获得中央主要领导批示多次,并获中央相关部门和省委相关部门采纳多次。

  • 研究领域

    数据科学;智能决策;人机共生智能

  • 教育背景

    2011   香港科技大学    计算机科学与工程学        博士

  • 代表性论文

    Mobile Targeting Using Customer Trajectory Patterns[J]. Management Science, 2019, 65(11): 5027-5049. (with Ghose A., Li B.)

    A Hierarchical 3D-Motion Learning Framework for Animal Spontaneous Behavior Mapping[J]. Nature Communications, 2021, 12(1): 2784. (with Huang K., Han Y., Chen K., et al.)

    CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction[J]. IEEE Transactions on Knowledge and Data Engineering, 2021, 35(4): 3484-3499. (with Xu X., Zhou F., Zhang K., et al.)

    Responsible IS by Design: A Psychology-Informed Social Connection Recommender System for Mental Health[C]. The 2021 INFORMS Workshop on Data Science(Best Paper Award),2021. (with Li J., Zhang K., et al.)

    Bitcoin Price Forecasting: A Perspective of Underlying Blockchain Transactions[J]. Decision Support Systems, 2021, 151: 113650. (with Guo H., Zhang D., et al.)

    Is It All About You or Your Driving? Designing IoT‐Enabled Risk Assessments[J]. Production and Operations Management, 2022, 31(11): 4205-4222. (with Ho Y., Pu J., et al.)

    Toward Robust Monitoring of Malicious Outbreaks[J]. INFORMS Journal on Computing, 2022, 34(2): 1257-1271. (with Tang S., Han X., et al.)

    CCGL: Contrastive Cascade Graph Learning[J]. IEEE Transactions on Knowledge and Data Engineering, 2022, 35(5): 1-15. ( with Xu X., Zhou F., Zhang K., et al.)

    Unsupervised Learning for Human Mobility Behaviors[J]. INFORMS Journal on Computing, 2022, 34(3): 1565-1586. (with Tang S., Zheng J., et al.)

    Semi-Supervised Anomaly Detection Via Neural Process[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(10): 10423-10435. (with Zhou F., Wang G., Zhang K., et al.)

    Counterfactual Graph Learning for Anomaly Detection on Attributed Networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(10): 10540-10553. (with Xiao C., Xu X., Lei Y., et al.)

    Fun Shopping: A Randomized Field Experiment on Gamification[J]. Information Systems Research, 2023, 34(2): 766-785. (with Ho Y., Wang L.)

    Relational Fusion-based Stock Selection with Neural Recursive Ordinary Differential Equation Networks[J]. Information Fusion, 2024, 110: 102468. (with Gao Q., Zhou X., Huang L., et al.)

    The Role of Monitoring Effect in Risk Classification: Evidence from Telematics Adoption [J]. Management Science. 2025. (with Lee H., Li X.)

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