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Zhepeng (Lionel) Li

Associate Professor in IIM, B-School, The University of Hong Kong

Greetings, my name sounds like ‘Dzerpon Lee’. I am working with a focus on the intersection of applied machine learning and business analytics/intelligence. My primary methods lie in the domain of ‘Geometric Machine Learning’, which covers a wide range of topical streams such as personalized recommendations, social network analytics, target marketing, PropTech, HR analytics, financial analytics, and distributed data mining with privacy protection. My research aims to address pertinent business and managerial challenges by approaching them through machine learning, predictive modeling and computational data science perspectives. My research paradigm involves formulating business questions into learning problems, analyzing the theoretical efficacy of proposed methods, developing machine learning methods and algorithms, and utilizing realistic data for benchmarking evaluations, ablation tests, experiments, and other empirical analyses.

Headline News

11/2022: Post-doc Position. Business ML Research Group is looking to hire a post-doc at the rank of Senior Research Assistant in Faculty of Business and Economics at The University of Hong Kong. Details are available at Careers HKU

Research Interests

  • Business Analytics - Data Analytics, Analytical Modeling, Optimization & Algorithms
  • Business Artificial Intelligence - Geometric Machine Learning, Predictive Modeling, Statistical Inference, 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 (Major in MIS, Minor in CS), University of Utah, Salt Lake City, United States, 2013
  • Master in Management Science & Engineering, University of Science and Technology of China, Hefei, China, 2007

Student Expectations

  • Self-motivation: doctoral students are expected to show passion and take the initiative in your own project(s).
  • Rigorous Creativity: doctoral students need to show novelty that survives technical, quantitative, or analytical examinations in a long run.
  • Maturity: graduate students need to show professionalism in communications and works.
  • Integrity: all students should assume the highest standard of integrity and ethics in all aspects of coursework and research. Absolute zero tolerance shall be committed at multiple levels.

As a result, your differentiating impact could be projected as shown below.
$$
\text{Input*} = \text{arg}\max_{input} \{ \lim_{i=0}^{\infty}\text{effort}_i + \delta(\text{gift}) + \epsilon(\text{luck}) - \gamma(\text{circumstances}) \}
$$

$$
\text{Impact} = \text{Delivery(input*)}\times \text{Novelty}
$$

Working Projects

  • Spatial Recommender Systems in Personalizations
  • Graphical Neural Network in PropTech
  • Credit Risk Analytics in FinTech
  • Collective Performance in HR Analytics
  • Human Mobility Analytics in Disaster Management
  • Text Analytics in Social Media