Digital Privacy in Personalized Pricing and New Directions in DeFI
Speakers
Chen Xi
Professor and Andre Meyer Faculty Fellow, Department of Technology, Operations, and Statistics, Stern School of Business, New York University.
Xi Chen is the Andre Meyer Full professor at Stern School of Business, New York University, who is also an affiliated professor at Computer Science and Center for Data Science. Before that, he was a Postdoc in the group of Prof. Michael Jordan at UC Berkeley and obtained his Ph.D. from the Machine Learning Department at Carnegie Mellon University.
He studies high-dimensional machine learning, online learning, large-scale stochastic optimization, and applications to operations management and FinTech. Recently, he started a new research line on blockchain technology and decentralized finance. He is a recipient of COPSS Leadership Academy, Elected Member of International Statistical Insititute (ISI), The World’s Best 40 under 40 MBA Professor by Poets & Quants, and Forbes 30 under 30 in Science.
| Date: |
| Tuesday, 2 January 2024 |
| Time: |
| 10:00 am - 11:30 am |
| Venue: |
|
Institute of Data Science Innovation 4.0 I4-01-03 (Level 1, Seminar Room) 3 Research Link Singapore 117602 (Map) |
Abstract
This talk has two parts. The first part is on digital privacy in personalized pricing. When involving personalized information, how to protect the privacy of such information becomes a critical issue in practice. In this talk, we consider a dynamic pricing problem with an unknown demand function of posted prices and personalized information. By leveraging the fundamental framework of differential privacy, we develop a privacy-preserving dynamic pricing policy, which tries to maximize the retailer revenue while avoiding information leakage of individual customers’ information and purchasing decisions. This is joint work with Prof. Yining Wang and Prof. David Simchi-Levi.
The second part is on my very recent research in decentralized finance. I will first discuss my work on delta hedging liquidity positions on the automated market maker (Uniswap V3) and then highlights some open problems in decentralized finance.