Dr. Lionel Zhepeng LI
Innovation and Information Management

External Data Scientist, Bank of Ning Bo (SZSE: 002142)
Associate Professor
3910 2404
zpli@hku.hk
KK 822
https://lionelyashiro.github.io


Academic & Professional Qualification
PhD in Operations & Information Systems, University of Utah, Salt Lake City, United States (Major in Information?Systems, Minor in Computer?Science)
Master in?Management Science & Engineering, University of Science and Technology of China, Hefei, China
Biography
Dr. Zhepeng (Lionel) Li is associate professor of Information Systems in the Faculty of Business and Economics. He received PhD degree in Operations and Information Systems from University of Utah in 2013. His research interests include computational data science, data mining, machine learning with applications in business analytics, recommendation and social network analytics. He has published in leading journals, such as Management Science, Information Systems Research, MIS Quarterly and ACM Transactions. His study is currently supported by the Discovery Grant of Natural Sciences and Engineering Research Council of Canada (NSERC) and National Natural Science Foundation of China (NSFC). He has received ISS design science research award of INFORMS in 2016 and served as organizer in the global research events such as program co-chair of INFORMS workshop on Data Science 2019 and Winter Conference of Business Analytics 2020, and chair of AI cluster of INFORMS 2021.
In particular, my research work is at the intersection of applied machine learning and business analytics/intelligence. Topics include recommendations, social network analytics, target marketing, PropTech, HR analytics, financial analytics, and distributed data mining with privacy protection. My interests revolve addressing relevant business and managerial problems from machine learning, predictive modelling and other computational data science perspectives. In this vein, my research paradigm encompasses formulating business domain questions into data-driven problems, analyzing the theoretical efficacy of the proposed methods, devising machine learning methods and/or algorithms, and using realistic data sets for benchmarking evaluations, ablation tests, experiments, or other empirical analyses.
Research Interest
Computational Data Science
Artificial Intelligence in Businesses
Recommender Systems
Information Privacy & Security
Selected Publications
Zhepeng (Lionel) Li, Yong Ge, Xue Bai. 2021. What Will be Popular Next? Predicting Hotspots in Two-mode Social Networks. MIS Quarterly* (MISQ)
Wade Cook, Wanghong Li, Zhepeng (Lionel) Li, Joe Zhu. 2021. Efficiency Measurement for Hierarchical Situations. Journal of the Operational Research Society (JORS).
Wade Cook, Wanghong Li, Zhepeng (Lionel) Li, Liang Liang, Joe Zhu. 2020. Efficiency Measurement with Products and Partially Desirably Co-Products. Journal of the Operational Research Society (JORS) 71(2): 335-345.
Zhepeng (Lionel) Li, Xiao Fang, and Olivia R. Liu Sheng. 2018. A Survey of Link Recommendation for Social Networks: Methods, Theoretical Foundations, and Future Research Directions. ACM Transactions on Management Information Systems (TMIS) 9(1): 1-26.
Zhepeng (Lionel) Li, Xiao Fang, Xue Bai, and Olivia R. Liu Sheng. 2017. Utility-based Link Recommendation for Online Social Networks. Management Science* (MS) 63(6): 1938-1952.
Wanghong Li, Zhepeng (Lionel) Li, Liang Liang, Wade D. Cook. 2017. Evaluation of Ecological Systems and the Recycling of Undesirable Outputs: An Efficiency Study of Regions in China. Socio-Economic Planning Sciences 60: 77-86.
Xiao Fang, Paul Hu, Zhepeng (Lionel) Li and Weiyu Tsai (Authors are of Equal Contribution). 2013. Predicting Adoption Probabilities in Social Networks. Information Systems Research* (ISR) 24(1): 128-145.
(* Area top-tier outlets)
Awards and Honours
INFORMS ISS Design Science 2016
PI,?Discovery Grant,?Natural Sciences and Engineering Research Council (NSERC) of Canada,?2017-2022
Co-PI, National Natural Science Foundation?(NSF) of?China, 2017-2020