Sotabase

Career

· Researcher, Massachusetts Institute of Technology (MIT) Katabi Lab2026–
· Assistant Professor, Massachusetts Institute of Technology2022–
· Assistant Professor in the Theory of Computing Group, Massachusetts Institute of Technology (MIT)2022–
· Researcher, Massachusetts Institute of Technology (MIT) Vision Group2022–
· Researcher / Faculty Spotlight, MIT CSAIL2022–
· Assistant Professor, MIT Department of Electrical Engineering and Computer Science (EECS) / CSAIL2022–
· Miller Fellow, University of California, Berkeley2018–2021
· PhD in Computer Science, Cornell University2013–2018
· B.S. in Computer Science and Mathematics, University of Washington2008–2013
· Researcher/Professor, Massachusetts Institute of Technology (MIT) - CSAIL
· Researcher, MIT Applied Computing Group
· Researcher, Model-Based Embedded and Robotics Systems Group (MERS)

Publications (0)

A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem
IEEE Annual Symposium on Foundations of Computer Science · 2016
266
cited
Mixture models, robustness, and sum of squares proofs
Symposium on the Theory of Computing · 2017
192
cited
Tensor principal component analysis via sum-of-square proofs
Annual Conference Computational Learning Theory · 2015
176
cited
The Power of Sum-of-Squares for Detecting Hidden Structures
IEEE Annual Symposium on Foundations of Computer Science · 2017
149
cited
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors
Symposium on the Theory of Computing · 2015
142
cited
Efficient Bayesian Estimation from Few Samples: Community Detection and Related Problems
IEEE Annual Symposium on Foundations of Computer Science · 2017
108
cited
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
Neural Information Processing Systems · 2019
106
cited
Mean estimation with sub-Gaussian rates in polynomial time
Annals of Statistics · 2018
87
cited
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent
Annual Conference Computational Learning Theory · 2020
71
cited
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization
Neural Information Processing Systems · 2020
70
cited
Efficient mean estimation with pure differential privacy via a sum-of-squares exponential mechanism
Symposium on the Theory of Computing · 2021
67
cited
Bayesian estimation from few samples: community detection and related problems
arXiv.org · 2017
62
cited
Robustness Implies Privacy in Statistical Estimation
Symposium on the Theory of Computing · 2022
62
cited
Robustly Learning any Clusterable Mixture of Gaussians
arXiv.org · 2020
47
cited
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics
Neural Information Processing Systems · 2022
42
cited
How Hard Is Robust Mean Estimation?
Annual Conference Computational Learning Theory · 2019
41
cited
Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond
Symposium on the Theory of Computing · 2019
39
cited
On the Integrality Gap of Degree-4 Sum of Squares for Planted Clique
ACM-SIAM Symposium on Discrete Algorithms · 2016
39
cited
Sub-Gaussian Mean Estimation in Polynomial Time
arXiv.org · 2018
37
cited
Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures
IEEE Annual Symposium on Foundations of Computer Science · 2020
30
cited
Sotabase