I am currently a forth (and final) year PhD student in Computer Science at Princeton University (where I also got my Master's degree), and I am fortunate to be advised by Matt Weinberg. I work on a broad set of problems that relate to online optimization, incentive, learning, and their intersection.
Prior to joining Princeton, I graduated with University Honors from University of Illinois at Urbana Champaign with a BS in Computer Science and a BSLAS in Mathematics.
Here is my CV.
Conference Publications

Optimal Stopping with MultiDimensional Comparative Loss
Aversion
Linda Cai, Joshua Gardner, S. Matthew Weinberg.
The 19th Conference On Web And InterNet Economics (WINE), 2023.

Selling to Multiple NoRegret Buyers
Linda Cai, S. Matthew Weinberg, Evan Wildenhain, Shirley Zhang.
The 19th Conference On Web And InterNet Economics (WINE), 2023.

Pandora's Problem with Nonobligatory Inspection: Optimal Structure and a PTAS.
Hedyeh Beyhaghi, Linda Cai.
In Proceedings of 55th Annual ACM Symposium on Theory of Computing (STOC), 2023.
[video] [short slides] [long slides]

The ShortSide Advantage in Random Matching Markets.
Linda Cai, Clayton Thomas.
In Proceedings of the SIAM Symposium on Simplicity in Algorithms (SOSA), 2022.
[slides]

99% Revenue with Constant Enhanced Competition.
Linda Cai, Raghuvansh R. Saxena.
In Proceedings of The TwentySecond ACM Conference on Economics and Computation (EC), 2021.
[video] [slides]

Implementation in Advised Strategies: Welfare Guarantees from PostedPrice Mechanisms when Demand Queries are NPhard.
Linda Cai, Clayton Thomas, S. Matthew Weinberg.
In Proceedings of the 11th Innovations in Theoretical Computer Science (ITCS), 2020.
[slides]

Baechi: fast device placement of machine learning graphs.
Beomyeol Jeon, Linda Cai, Pallavi Srivastava, Jintao Jiang, Xiaolan Ke, Yitao Meng, Cong Xie, Indranil Gupta.
In Proceedings of ACM Symposium on Cloud Computing (SOCC), 2020.
[slides]
Survey Papers
Teaching
I have TA'd for the following courses at Princeton University: