Jeff Cai is the Patricia and George Scharpf Family Assistant Professor in Real Estate in the IT, Analytics, and Operations Department (ITAO). Jeff received his PhD in Statistics and Data Science from the Wharton School at the University of Pennsylvania. His research lies in the intersection of statistical learning and data-driven decision-making, with applications to revenue management, corporate governance, healthcare, and urban studies. A significant thrust of his research is on sequential decision-making (bandits, reinforcement learning), network analysis, model selection and post-selection inference. Notably, his work involves constructing inter-firm networks, such as dynamic equity investment networks of all 40 million firms in China, to examine network effects on corporate behavior and decisions.
Jeff is passionate about teaching and has been teaching a statistical learning course at different levels, from pre-college, undergraduates, graduates and MBAs, to executive education, which has been recognized with teaching awards at both Mendoza and Wharton. At Mendoza, he teaches machine learning in urban analysis (an elective for the business analytics major and real estate minor) in spring semesters.
"Doubly High-Dimensional Contextual Bandits: An Interpretable Model with Applications to Assortment and Pricing", Conference on Artificial Intelligence, Machine Learning, and Business Analytics, Yale University, 2024
"Optimal Assortment and Pricing via Generalized MNL Models with Poisson Arrival", ESIF Economics and AI+ML Meeting, Cornell University, 2024
"Personalized Reinforcement Learning: WIth Applications to Recommender Systems", IMS International Conference on Statistics and Data Science (ICSDS), 2023
"Doubly High-Dimensional Contextual Bandits: An Interpretable Model with Applications to Assortment and Pricing", Manufacturing and Service Operations Management Conference, 2023
"Personalized Reinforcement Learning: With Applications to Recommendation Systems", Statistics Empowering Data Science (SEEDS) Conference, University of Southern California, 2023
"Ownership network and firm growth: What do forty million companies tell about the Chinese economy?", Annual Meeting of American Finance Association (AFA) 2021, 2021
"Centralization or decentralization? The evolution of state-ownership in China", China International Conference in Finance (CICF) 2021, 2021
"Ownership network and firm growth: What do forty million companies tell about the Chinese economy?", The Sixth Network Science in Economics Conference 2021, 2021
"Network Regression and Supervised Centrality Estimation", Young Scholars Conference on Machine Learning in Economics and Finance, Federal Reserve Bank of Philadelphia, 2021
"Ownership network and firm growth: What do forty million companies tell about the Chinese economy?", Annual Meeting of Midwest Finance Association (MFA) 2020, 2020
"Ownership network and firm growth: What do forty million companies tell about the Chinese economy?", NBER Chinese Economy Meeting 2020, 2020
"Nonparametric Empirical Bayes Methods for Sparse and Noisy Signals", The Fourth Workshop on Higher-Order Asymptotics and Post-Selection Inference (WHOA-PSI-4), Washington University of St. Louis, 2019, 2019
"Innovation and Equity Holding Network", Workshop on Innovation and Intellectual Property: Firm Strategies and Policy Challenges in a Rapidly Changing World, Beijing, 2019, 2019
Award
"MSBA Outstanding Professor Award", Mendoza College of Business, 2025
"Best Paper Award", China Financial Research Conference (CFRC), 2021
"Murray Teaching Award", The Wharton School, University of Pennsylvania, 2021
"XiYue Best Paper Award", China International Conference in Finance (CICF), 2021
"Mack Institute Research Fellowship", Mack Institute for Innovation Management, 2020
"George James Term Fund Award", The Wharton School, University of Pennsylvania, 2019
