About me

I am Zhepeng (Lionel) Li, pronouncing as 'Dzerpon Lee'


"My research is broadly at the intersection of applied machine learning and business analytics/intelligence. Specific topics include recommendations, social network analytics, target marketing, PropTech, HR analytics, financial analytics, and distributed data mining with privacy protection. My interests are in addressing relevant business and managerial problems from machine learning, predictive modelling and other computational data science perspectives. Hence, my research paradigm encompasses formulating business questions into learning problems, analyzing the theoretical efficacy of the proposed methods, devising machine learning methods and algorithms, and using realistic data for benchmark evaluation and empirical analysis. "

Research Interests:

  • Business Analytics - Data Analytics, Analytical Modeling, Optimization & Algorithms

  • Business Artificial Intelligence - Predictive Modeling, Statistical Inference, Machine Learning, Social Media/Network Analytics, FinTech, PropTech, HR Analytics etc.

  • Personalizations - Recommender Systems, Web/Text Mining

  • Information Privacy and Security - Sensitive Data Sharing, Privacy-Preserving Data Mining

Education:

  • PhD in Operations & Information Systems, University of Utah, Salt Lake City, United States, 2013 (Major in MIS, Minor in CS)

  • Master in Management Science & Engineering, University of Science and Technology of China, Hefei, China, 2007

Work Experience:

  • Associate Professor in Information Systems, Schulich School of Business, York University, Toronto, Canada 2019 - present

  • Assistant Professor in Information Systems, Schulich School of Business, York University, Toronto, Canada 2014 - 2019

Bio

Zhepeng (Lionel) Li is associate professor of Management Information System in the Schulich School of Business at York University, Toronto, Canada. He received PhD degree in operations and information systems from University of Utah in 2013. His research interests include data mining, machine learning and computational data science with applications on business analytics, recommendation and social network analytics. He has published in premier journals including 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). He has received design science research award of INFORMS in 2016 and co-chaired programs of INFORMS workshop on Data Science and Winter Conference of Business Analytics.