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Tao Lin
PhD in Computer Science
About Me
Starting in July 2025, I will be a postdoctoral researcher at Microsoft Research, in the Economics and Computation group in New England, hosted by Alex Slivkins.
I obtained my PhD degree in Computer Science from Harvard University, where I am very fortunate to be advised by Yiling Chen. My research lies in the intersection between economics and machine learning. I have been working on “mechanism design + machine learning” problems since my undergraduate study at Peking University, working with Xiaotie Deng. Recently, I focused more on information design problems, like Bayesian persuasion. I also investigate the incentive issues in real-world machine learning systems, such as ad auction platforms and recommender systems. From 2023 to 2024, I interned at ByteDance and Google. I received the Siebel Scholarship in 2024.
I will be an assistant professor in the School of Data Science at the Chinese University of Hong Kong, Shenzhen, starting in 2026.
Contact: tlin@g.harvard.edu
Interests
- Information Design
- Mechanism Design
- Machine Learning
Education
- PhD in Computer Science
Harvard University - BSc in EECS
Peking University
🗞️ News
- [2025/6] I am co-organizing a workshop on Information Economics x LLMs at EC'25. Submissions and participation are welcome!
- [2025/4] I will attend ICLR'25 in Singapore to present our spotlight paper “Generalized Principal-Agent Problem with a Learning Agent”!
- [2025/1] I will attend ITCS'25 in New York to present our work “Information Design with Unknown Prior”; see video.
- ….
📚 My Research
My research direction is Learning-Based Incentive Design. It is motivated by the question of “_how to design a multi-agent system so that self-interested agents are incentivized to achieve a globally desirable outcome_”. In particular, I study mechanism design and informamtion design problems with machine-learning-based decision-makers. I am also fascinated by the incentive issues in real-world machine learning systems, such as ad auction platforms and recommender systems.
📃 Conference Publications
(Alphabetical) Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira (2024).Bias Detection via Signaling.Advances in Neural Information Processing Systems (NeurIPS).
🎙️ Recent & Upcoming Talks
Nov 15, 2024
Oct 20, 2024
Oct 10, 2024
Aug 17, 2023
Jun 14, 2023
Experience
Postdoctoral Researcher
Microsoft Research July 2025 – July 2026
2. ### Student Researcher
Google June 2024 – September 2024
3. ### Research Intern
ByteDance May 2023 – August 2023
Education
PhD in Computer Science
Harvard University September 2020 – May 2025
2. ### BSc in EECS
Peking University September 2016 – July 2020