Digital Privacy in Personalized Pricing and New Directions in Web3

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 Professor Yining Wang and Professor David Simchi-Levi.

The second part is on my research in Web3, in particular, 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.