Speakers
Zhi Wang
McCombs School of Business, University of Texas at Austin
Zhi Wang is a Postdoctoral Fellow at Rotman School of Management at University of Toronto, supervised by Prof. Ming Hu. She earned her PhD in Decision Science at McCombs School of Business, UT Austin, where she was advised by Prof. Rui Gao. Prior to PhD, she obtained a B.E. honours degree from SUTD. Her research focuses on developing reliable AI solutions that are both analytically rigorous and empirically effective for addressing real-world operational challenges, especially in revenue management and consumer choice models. She applies tools from machine learning theory, data-driven optimization, and statistics to choice modeling, pricing, assortment, and e-commerce platform applications. These include her industry experience with Expedia Pricing Team and Rakuten Advertising Team.
| Date: |
| Tuesday, 25 November 2025 |
| Time: |
| 10:00 am - 11:30 am |
| Venue: |
|
NUS Business School Mochtar Riady Building BIZ1 0302 15 Kent Ridge Drive Singapore 119245 (Map) |
Abstract
Discrete choice models are a core tool in operations, marketing, and economics for understanding consumer behavior, supporting demand forecasting and revenue optimization. However, learning these models remains challenging due to the complexity of human decision-making. Motivated by recent advances in AI, we leverage neural networks (NNs) to model rich behavioral nuances, particularly consumer taste heterogeneity and bounded rationality. Our frameworks harmonize the flexibility and scalability of NNs with strong theoretical soundness, such as generalization guarantees and global algorithmic convergence. Empirical studies substantiate our theoretical results, and our algorithmic framework also sheds light on other operations problems, such as assortment optimization.