Sitan Chen

I am an NSF postdoc at UC Berkeley hosted by Prasad Raghavendra. In Fall of 2023, I will join the Theory of Computation group at Harvard's John A. Paulson School of Engineering and Applied Sciences as an Assistant Professor of Computer Science.

I work on designing algorithms with provable guarantees for fundamental problems in data science, especially in the context of generative modeling, robustness, and deep learning. I also enjoy exploring what techniques for such problems can tell us about inverse problems in the sciences, most recently with regards to understanding the capabilities of near-term quantum devices.

I received my PhD in EECS from MIT as a member of CSAIL and the Theory of Computation group. I was very fortunate to be advised by Ankur Moitra and supported by an MIT Presidential Fellowship and a PD Soros Fellowship. Prior to MIT, I studied mathematics and computer science as an undergraduate at Harvard, where I had the pleasure and honor of working with Salil Vadhan and Leslie Valiant.

Email: sitan (at) seas (dot) harvard (dot) edu


Papers (authors alphabetical unless not):

  1. Learning Polynomial Transformations [pdf] [video]
    Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang
    In submission
  2. Sampling Is as Easy as Learning the Score: Theory for Diffusion Models With Minimal Data Assumptions [pdf]
    Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang
    ICLR 2023
    Oral presentation
  3. Learning to Predict Arbitrary Quantum Processes [pdf]
    Hsin-Yuan Huang, Sitan Chen, John Preskill
    QIP 2023
  4. The Complexity of NISQ [pdf]
    Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
    QIP 2023
  5. Tight Bounds for State Tomography with Incoherent Measurements [pdf]
    Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke
    QIP 2023, merged with [CHLL22]
  6. Learning (Very) Simple Generative Models Is Hard [pdf]
    Sitan Chen, Jerry Li, Yuanzhi Li
    NeurIPS 2022
    Oral presentation
  7. Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks [pdf]
    Sitan Chen, Aravind Gollakota, Adam R. Klivans, Raghu Meka
    NeurIPS 2022
    Oral presentation
  8. Tight Bounds for Quantum State Certification with Incoherent Measurements [pdf]
    Sitan Chen, Brice Huang, Jerry Li, Allen Liu
    FOCS 2022, QIP 2023
  9. Quantum Advantage in Learning From Experiments [pdf] [journal]
    Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean
    Science
  10. Kalman Filtering with Adversarial Corruptions [pdf]
    Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
    STOC 2022
  11. Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs [pdf]
    Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka
    ICLR 2022
  12. A Hierarchy for Replica Quantum Advantage [pdf]
    Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
    QIP 2022, merged with [CCHL21]
  13. Towards Instance-Optimal Quantum State Certification With Independent Measurements [pdf]
    Sitan Chen, Jerry Li, Ryan O'Donnell
    QIP 2022, COLT 2022
    Blurb on Property Testing Review
  14. Symmetric Sparse Boolean Matrix Factorization and Applications [pdf]
    Sitan Chen, Zhao Song, Runzhou Tao, Ruizhe Zhang
    ITCS 2022
  15. Efficiently Learning One Hidden Layer ReLU Networks From Queries [pdf]
    Sitan Chen, Adam R. Klivans, Raghu Meka
    NeurIPS 2021
  16. Exponential Separations Between Learning With and Without Quantum Memory [pdf]
    Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li
    FOCS 2021, QIP 2022
    Invited to SIAM Journal of Computing Special Issue
  17. Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination [pdf]
    Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
    FOCS 2021
  18. Learning Deep ReLU Networks Is Fixed-Parameter Tractable [pdf] [video]
    Sitan Chen, Adam R. Klivans, Raghu Meka
    FOCS 2021
  19. Algorithmic Foundations for the Diffraction Limit [pdf] [slides] [code] [video] [Ankur's Simons tutorial]
    Sitan Chen, Ankur Moitra
    STOC 2021
  20. On InstaHide, Phase Retrieval, and Sparse Matrix Factorization [pdf]
    Sitan Chen, Xiaoxiao Li, Zhao Song, Danyang Zhuo
    ICLR 2021
  21. Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability [pdf] [code] [Ankur's Simons tutorial]
    Sitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
    NeurIPS 2020
    Spotlight presentation
  22. Learning Structured Distributions from Untrusted Batches: Faster and Simpler [pdf] [code]
    Sitan Chen, Jerry Li, Ankur Moitra
    NeurIPS 2020
  23. Entanglement is Necessary for Optimal Quantum Property Testing [pdf] [slides] [video]
    Sebastien Bubeck, Sitan Chen, Jerry Li
    FOCS 2020
    Blurb on Property Testing Review
  24. Learning Polynomials of Few Relevant Dimensions [pdf] [slides] [video]
    Sitan Chen, Raghu Meka
    COLT 2020
  25. Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments [pdf] [slides] [video]
    Sitan Chen, Jerry Li, Zhao Song
    STOC 2020
  26. Efficiently Learning Structured Distributions from Untrusted Batches [pdf] [slides] [video]
    Sitan Chen, Jerry Li, Ankur Moitra
    STOC 2020
  27. Improved Bounds for Sampling Colorings via Linear Programming [pdf] [slides]
    Sitan Chen, Michelle Delcourt, Ankur Moitra, Guillem Perarnau, Luke Postle
    (merger of [CM18] and [DPP18])
    SODA 2019
  28. Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications [pdf] [slides]
    Sitan Chen, Ankur Moitra
    STOC 2019
  29. Basis Collapse For Holographic Algorithms over All Domain Sizes [pdf] [slides] [video]
    Sitan Chen
    STOC 2016.
  30. Pseudorandomness for Read-Once, Constant-Depth Circuits [pdf]
    Sitan Chen, Thomas Steinke, Salil Vadhan
    Manuscript

Theses:

  • Rethinking Algorithm Design for Modern Challenges in Data Science [pdf]
    PhD Thesis, 2021
  • Geometry in Algorithms and Complexity: Holographic Algorithms and Valiant's Conjecture [pdf]
    Undergraduate Thesis, 2016
    Thomas Hoopes Prize, Captain Jonathan Fay Prize (for best Harvard undergraduate theses), New World Mathematics Award

Service:

  • PC Member: FOCS 2022, ICALP 2022

Other:

 
picture of me