Yiding Feng 冯逸丁

Postdoctoral Researcher, Microsoft Research New England

yidingfeng@microsoft.com              CV                      Google Scholar Profile

Hi! I am a postdoctoral researcher at Microsoft Research New England. I previously received my PhD [thesis] from Department of Computer Science, Northwestern University in 2021 where my advisor was Jason D. Hartline. Before that, I received my BS degree from ACM Honors Class at Shanghai Jiao Tong University.

My current research focuses on examining commonly used algorithms/mechanisms and developing new ones in various online marketplaces, taking into account potential concerns or features from uncertainties, incentives, competition, or presence of highly detailed user data. As an interdisciplinary researcher, I approach these marketplaces with a fresh perspective as well as novel ideas from operations, economics, and computer science. Through collaboration wth researchers in both academia and industry, I have primarily addressed problems in online decision making, mechanism & information design, and optimization.

I will be joining HKUST IEDA as an assistant professor in 2024!

Preprints & Papers under Review

Batching and Optimal Multi-stage Bipartite Allocations

Near-optimal Bayesian Online Assortment of Reusable Resources

Bias-Variance Games

Dynamic Pricing and Learning with Bayesian Persuasion

Mobility Data in Operations: The Facility Location Problem

Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response

Online Assortment of Reusable Resources with Exogenous Replenishment

Journal Articles

Two-stage Matching and Pricing with Applications to Ride Hailing

Controlling Epidemic Spread: Reducing Economic Losses with Targeted Closures

Conference Proceedings

Online Resource Allocation with Buyback: Optimal Algorithms via Primal-Dual

Simple Mechanisms for Agents with Non-linear Utilities

Competitive Information Design for Pandora's Box

Online Bayesian Recommendation with No Regret

Near-optimal Bayesian Online Assortment of Reusable Resources

Bias-Variance Game

Revelation Gap for Pricing from Samples

Batching and Optimal Multi-stage Bipartite Allocations

Two-stage Matching and Pricing with Applications to Ride Hailing

Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models

Optimal Auctions vs. Anonymous Pricing: Beyond Linear Utility

An End-to-end Argument in Mechanism Design (Prior-independent Auctions for Budgeted Agents)