I am currently a postdoctoral researcher at UC Berkeley, where I am fortunate to be hosted by Michael I. Jordan. I work on a broad set of problems that relate to online optimization, incentive, learning, and their intersection.

Prior to joining Berkeley, I was a PhD student in Computer Science at Princeton University (where I also got my Master's degree), and I was fortunate to work with my advisor Matt Weinberg and many wonderful collaborators. Prior to my PhD, 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 and Preprints

• Faster Diffusion-based Sampling with Randomized Midpoints: Sequential and Parallel
  Shivam Gupta, Linda Cai, Sitan Chen.
  In submission to ICLR, 2025.
• Profitable Manipulations of Cryptographic Self-Selection are Statistically Detectable
  Linda Cai, Jingyi Liu, S. Matthew Weinberg, Chenghan Zhou.
  The 6th international conference on Advances in Financial Technologies (AFT), 2024.
• Bundling in Oligopoly: Revenue Maximization with Single-Item Competitors
  Moshe Babaioff, Linda Cai, Brendan Lucier.
  The 25th ACM Conference on Economics and Computation (EC), 2024.
  [slides]
• Selling to Multiple No-Regret Buyers
  Linda Cai, S. Matthew Weinberg, Evan Wildenhain, Shirley Zhang.
  The 19th Conference On Web And InterNet Economics (WINE), 2023.
  [slides]
• Optimal Stopping with Multi-Dimensional Comparative Loss Aversion
  Linda Cai, Joshua Gardner, S. Matthew Weinberg.
  The 19th Conference On Web And InterNet Economics (WINE), 2023.
  [slides]
• 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 Short-Side 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 Twenty-Second ACM Conference on Economics and Computation (EC), 2021.
  [video]   [slides]
• Implementation in Advised Strategies: Welfare Guarantees from Posted-Price Mechanisms when Demand Queries are NP-hard.
  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

• Recent Developments in Pandora’s Box Problem: Variants and Applications.
  Hedyeh Beyhaghi, Linda Cai.
  SIGecom Exchanges Vol. 21.1, 2023.

Teaching

I have TA'd for the following courses at Princeton University:

• COS 521 - Advanced Algorithms Design, Fall 2021.
• COS 445 - Economics and Computing, Spring 2020.
• COS 451 - Computational Geometry, Fall 2019.
• COS 445 - Economics and Computing, Spring 2019.
• COS 126 - Computer Science: An Interdisciplinary Approach, Fall 2018.