Tao Lin

PhD student in Computer Science

Harvard University

Biography

I am a second-year PhD student in Computer Science at Harvard University, where I am very fortunate to be advised by Yiling Chen. I received my bachelor’s degree in EECS at Peking University. I am exploring theoretical computer science and machine learning. My current research interest lies in the intersection between economics and computation, particularly on algorithmic game theory.

Interests

Algorithmic Game Theory
Mechanism Design
Machine Learning

Education

BSc in EECS, 2020

Peking University

Publications

Xiaotie Deng, Xinyan Hu, Tao Lin, Weiqiang Zheng (2022). Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions. The Web Conference (WWW).

Manon Revel, Tao Lin, Daniel Halpern (2022). How Many Representatives Do We Need? The Optimal Size of an Epistemic Congress. AAAI.

Xiaotie Deng, Ron Lavi, Tao Lin, Qi Qi, Wenwei Wang, Xiang Yan (2020). A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling. NeurIPS.

PDF Slides arXiv publisher site

Hu Fu, Tao Lin (2020). Learning Utilities and Equilibria in Non-Truthful Auctions. NeurIPS.

PDF arXiv publisher site

Xiaotie Deng, Tao Lin, Tao Xiao (2020). Private Data Manipulation in Optimal Sponsored Search Auction. The Web Conference (WWW).

Working Papers

Xiaotie Deng, Yotam Gafni, Ron Lavi, Tao Lin, Hongyi Ling (2021). From Monopoly to Competition: Optimal Contests Prevail. Working paper.

Notes (not intended to publish)

Xiaoming Li, Tao Lin (2019). On Clearing Prices in Matching Markets: A Simple Characterization without Duality. Notes.

Talks

Robustness of Empirical Revenue Maximization in Auction Learning

Dec 23, 2020 Institute for Theoretical Computer Science (ITCS), SUFE

Experience

Research Intern

University of British Columbia

Jun 2019 – Sep 2019 Vancouver

Advised by Hu Fu.

Research Assistant

Center on Frontiers of Computing Studies, Peking University

Sep 2018 – Sep 2021 Beijing

Advised by Xiaotie Deng.