PeopleofSuperintelligence

Researcher

Tselil Schramm

Tselil Schramm is an assistant professor of statistics at Stanford whose research examines algorithms for machine learning and high-dimensional estimation. She earned a BSc at Harvey Mudd College in 2012 and a computer science PhD at UC Berkeley in 2017, then held postdoctoral positions at Harvard and MIT. Her 2021 work with Matthew Brennan, Guy Bresler, Sam Hopkins and Jerry Li connected statistical query algorithms with low-degree polynomial tests. She received an NSF CAREER award in 2022 for work on optimal estimators using sum-of-squares proof systems. With Misha Ivkov, she coauthored a STOC 2025 paper on robust approximate message passing; her 2026 paper with Eric Ma studied efficient sampling in models with disorder chaos.

Works
77
Citations
1,190
h-index
15
Badges

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

  1. 2012–2017

    Harvey Mudd and Berkeley degrees

    She earns a BSc at Harvey Mudd College in 2012. In 2017, she completes a PhD in UC Berkeley’s Computer Science Department, advised by Prasad Raghavendra and Satish Rao.

  2. By 2020

    Postdoctoral work at Harvard and MIT

    By 2020, she completes postdoctoral appointments at Harvard and MIT, hosted by Boaz Barak, Jon Kelner, Ankur Moitra and Pablo Parrilo.

  3. 2020

    Research visits and Simons fellowship

    In 2020, Schramm holds visiting researcher positions at the Weizmann Institute of Science and Microsoft Research’s Machine Learning and Optimization Group. She also serves as a Microsoft Research Fellow at the Simons Institute for the Theory of Computing, in its Probability, Geometry and Computation in High Dimensions program.

  4. 2021

    Joining Stanford Statistics

    In January 2021, she joins Stanford University’s Department of Statistics as an assistant professor. In 2021, she also serves as a visiting scientist and program organizer for Computational Complexity of Statistical Inference at the Simons Institute for the Theory of Computing.

  5. 2021

    Statistical queries and polynomial tests

    With Matthew Brennan, Guy Bresler, Sam Hopkins and Jerry Li, she coauthors “Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent” at COLT in 2021. The paper shows that, under mild conditions, statistical query algorithms and low-degree polynomial tests have essentially equivalent power for high-dimensional hypothesis testing, and receives Best Paper Runner Up at COLT 2021.

  6. 2022

    An NSF CAREER award

    In 2022, she receives an NSF CAREER award for “Optimal Estimators Using Sum-of-Squares Proof Systems.”

  7. 2025

    Robust approximate message passing

    With Misha Ivkov, she coauthors “Fast, robust approximate message passing” at STOC in 2025. The work gives a fast spectral procedure that makes approximate message passing algorithms robust to changes confined to a small principal submatrix of the input.

  8. 2026

    Sampling with disorder chaos

    In 2026, she and Eric Ma publish “Polynomial-time sampling despite disorder chaos” at COLT. They show that, with high probability, Glauber dynamics can efficiently sample from a hardcore model on a random graph with disorder chaos. In this setting, small random changes to the graph cause large changes to the sampling distribution.

  9. 2026

    Teaching statistics at Stanford

    In 2026, she teaches Theory of Statistics II and Literature of Statistics at Stanford. She is an assistant professor in Stanford’s Department of Statistics, with courtesy appointments in Computer Science and Mathematics. She studies algorithms for high-dimensional estimation, including machine learning, and the tradeoffs between information and computation.

Career

  1. Since 2021Stanford UniversityAssistant Professor
  2. NowStanford UniversityAssistant Professor of Computer Science and Mathematics (by courtesy)
  3. 2021University of California, BerkeleyVisiting Scientist and Program Organizer, Computational Complexity of Statistical Inference
  4. 2020Weizmann Institute of ScienceVisiting Researcher
  5. 2020Microsoft ResearchVisiting Researcher
  6. 2020University of California, BerkeleyMicrosoft Research Fellow, Simons Institute for the Theory of Computing
  7. Harvard UniversityPostdoctoral researcher
  8. Massachusetts Institute of TechnologyPostdoctoral researcher

Education

  1. 2017University of California, BerkeleyPhD in computer science
  2. 2012Harvey Mudd CollegeBSc

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Checked career sources: statistics.stanford.edu, simons.berkeley.edu, tselilschramm.org.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Tselil Schramm yet. Send us a free-licensed photo.

  1. About the Authors: Theory of Computing: An Open Access Electronic Journal in Theoretical Computer Science theoryofcomputing.org. Checked 27 October 2026.
  2. Tselil Schramm tselilschramm.org. Checked 27 October 2026.
  3. New Assistant Professor Tselil Schramm joins in January | Department of Statistics statistics.stanford.edu. Checked 27 October 2026.
  4. Tselil Schramm | Simons Institute for the Theory of Computing simons.berkeley.edu. Checked 27 October 2026.
  5. Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent proceedings.mlr.press. Checked 27 October 2026.
  6. Microsoft at COLT 2021 - Microsoft Research microsoft.com. Checked 27 October 2026.
  7. NSF CAREER funding awarded to Tselil Schramm | Department of Statistics statistics.stanford.edu. Checked 27 October 2026.
  8. STOC 2025 - 57th ACM Symposium on Theory of Computing acm-stoc.org. Checked 27 October 2026.
  9. [2411.02764] Fast, robust approximate message passing arxiv.org. Checked 27 October 2026.
  10. Polynomial-time sampling despite disorder chaos proceedings.mlr.press. Checked 27 October 2026.
  11. Tselil Schramm | Department of Statistics statistics.stanford.edu. Checked 27 October 2026.