Jason Gaitonde


Email: gaitonde AT mit DOT edu

I am a Postdoctoral Associate and Instructor in the Department of Mathematics at MIT, where I work with Elchanan Mossel. Previously, I received my PhD from the Department of Computer Science at Cornell University, where I was very fortunate to be advised by Éva Tardos. Even before that, I graduated from Yale University with degrees in Mathematics (B.S., with distinction) and Economics (B.A.).

I am broadly interested in theoretical computer science. In particular, my research focuses on theoretical problems at the intersection of algorithms, learning, game theory, networks, and randomness.


Papers
    Preprints
  1. Comparison Theorems for the Mixing Times of Systematic and Random Scan Dynamics, with Elchanan Mossel.
    Preprint.
    [Abstract]    [PDF]
  2. Efficiently Learning Markov Random Fields from Dynamics, with Ankur Moitra and Elchanan Mossel.
    Preprint.
    [Abstract]    [PDF]
  3. Sample-Efficient Linear Regression with Self-Selection Bias, with Elchanan Mossel.
    In submission.
    [Abstract]    [PDF]

  4. Journal Papers
  5. Bounds on the Covariance Matrix of the Sherrington-Kirkpatrick Model, with Ahmed El Alaoui.
    Electronic Communications in Probability 2024.
    [Abstract]    [PDF]
  6. The Price of Anarchy of Strategic Queuing Systems, with Éva Tardos.
    Journal of the ACM 2023 (JACM 2023)
    [Abstract]    [PDF]

  7. Conference Papers
  8. A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width, with Elchanan Mossel.
    Symposium on Theory of Computing 2024 (STOC 2024) .
    [Abstract]    [PDF]
  9. Budget Pacing in Repeated Auctions: Regret and Efficiency without Convergence, with Yingkai Li, Bar Light, Brendan Lucier, and Aleksandrs Slivkins.
    Innovations in Theoretical Computer Science 2023 (ITCS 2023).
    [Abstract]    [PDF]    [ITCS Talk]
  10. Eigenstripping, Spectral Decay, and Edge-Expansion on Posets, with Max Hopkins, Tali Kaufman, Shachar Lovett, and Ruizhe Zhang.
    International Conference on Randomization and Computation 2022 (RANDOM 2022).
    [Abstract]    [PDF]
  11. Fractional Pseudorandom Generators from Any Fourier Level, with Eshan Chattopadhyay, Chin Ho Lee, Shachar Lovett, and Abhishek Shetty.
    Computational Complexity Conference 2021 (CCC 2021).
    [Abstract]    [PDF]    [CCC Talk]
  12. Virtues of Patience in Strategic Queuing Systems, with Éva Tardos.
    The Twenty-Second ACM Conference on Economics and Computation (EC 21).
    [Abstract]    [PDF]    [EC Talk]
  13. Polarization in Geometric Opinion Dynamics, with Jon Kleinberg and Éva Tardos.
    The Twenty-Second ACM Conference on Economics and Computation (EC 21).
    [Abstract]    [PDF]    [EC Talk]
  14. Stability and Learning in Strategic Queuing Systems, with Éva Tardos.
    The Twenty-First ACM Conference on Economics and Computation (EC 20).
    [Abstract]    [PDF]    [EC Talk]
  15. Adversarial Perturbations of Opinion Dynamics in Networks, with Jon Kleinberg and Éva Tardos.
    The Twenty-First ACM Conference on Economics and Computation (EC 20).
    [Abstract]    [PDF]    [EC Talk]

Teaching