World's Best Scientists 2026 revealed!
David Steurer

David Steurer

D-Index & Metrics

Computer Science

D-Index
37
Citations
5150
World Ranking
10856
National Ranking
189

Research.com Recognitions

  • 2014 - Fellow of Alfred P. Sloan Foundation

Overview

David Steurer is affiliated with ETH Zurich in Switzerland and has contributed extensively to research in computer science, mathematics, and engineering. Their publication record highlights a focus on areas such as artificial intelligence, statistics and probability, and computational mechanics.

Key topics of research include:

  • Sparse and Compressive Sensing Techniques
  • Machine Learning and Algorithms
  • Random Matrices and Applications
  • Statistical Methods and Inference
  • Distributed Sensor Networks and Detection Algorithms
  • Complexity and Algorithms in Graphs
  • Stochastic Processes and Statistical Mechanics

Steurer's work has appeared prominently in venues such as arXiv (Cornell University), the Repository for Publications and Research Data at ETH Zurich, and the Leibniz-Zentrum für Informatik (Schloss Dagstuhl). The following recent papers illustrate the scope of their research:

  • Randomness Efficient Noise Stability and Generalized Small Bias Sets, 2020, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks, 2020, arXiv (Cornell University)
  • Reaching Kesten-Stigum Threshold in the Stochastic Block Model under Node Corruptions, 2023, arXiv (Cornell University)
  • Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers, 2021, Repository for Publications and Research Data (ETH Zurich)
  • Consistent regression when oblivious outliers overwhelm, 2020, arXiv (Cornell University)

Frequent collaborators include Tommaso d'Orsi, Jingqiu Ding, Stefan Tiegel, Gleb Novikov, and Rajai Nasser, indicating engagement in collaborative research efforts across different subfields.

Steurer's scholarly contributions cover several subfields within their primary areas, such as:

  • Artificial Intelligence
  • Statistics and Probability
  • Computational Mechanics
  • Computer Networks and Communications
  • Computational Theory and Mathematics

Recognition in their field includes being named a Fellow of the Alfred P. Sloan Foundation in 2014, a distinction awarded without a specified citation year.

Best Publications

  • Analytical approach to parallel repetition

    Irit Dinur;David Steurer

  • Subexponential Algorithms for Unique Games and Related Problems

    Sanjeev Arora;Boaz Barak;David Steurer

  • Graph expansion and the unique games conjecture

    Prasad Raghavendra;David Steurer

  • Hypercontractivity, sum-of-squares proofs, and their applications

    Boaz Barak;Fernando G.S.L. Brandao;Aram W. Harrow;Jonathan Kelner

  • Lower Bounds on the Size of Semidefinite Programming Relaxations

    James R. Lee;Prasad Raghavendra;David Steurer

  • Unique games on expanding constraint graphs are easy: extended abstract

    Sanjeev Arora;Subhash A. Khot;Alexandra Kolla;David Steurer

  • Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method

    Boaz Barak;Jonathan A. Kelner;David Steurer

  • Tensor principal component analysis via sum-of-square proofs.

    Samuel B. Hopkins;Jonathan Shi;David Steurer

  • Rounding Semidefinite Programming Hierarchies via Global Correlation.

    Boaz Barak;Prasad Raghavendra;David Steurer

  • Sum-of-squares proofs and the quest toward optimal algorithms.

    Boaz Barak;David Steurer

  • Message-Passing Algorithms and Improved LP Decoding

    S. Arora;C. Daskalakis;D. Steurer

  • Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors

    Samuel B. Hopkins;Tselil Schramm;Jonathan Shi;David Steurer

  • Efficient Bayesian Estimation from Few Samples: Community Detection and Related Problems

    Samuel B. Hopkins;David Steurer

  • Reductions between Expansion Problems

    Prasad Raghavendra;David Steurer;Madhur Tulsiani

  • The Power of Sum-of-Squares for Detecting Hidden Structures

    Samuel B. Hopkins;Pravesh K. Kothari;Aaron Potechin;Prasad Raghavendra

  • Robust moment estimation and improved clustering via sum of squares

    Pravesh K. Kothari;Jacob Steinhardt;David Steurer

  • Approximate Constraint Satisfaction Requires Large LP Relaxations

    Siu On Chan;James R. Lee;Prasad Raghavendra;David Steurer

  • Integrality Gaps for Strong SDP Relaxations of UNIQUE GAMES

    Prasad Raghavendra;David Steurer

  • Approximation Limits of Linear Programs (Beyond Hierarchies)

    Gábor G. Braun;Samuel Fiorini;Sebastian S. Pokutta;David D. Steurer

  • Rounding sum-of-squares relaxations

    Boaz Barak;Jonathan A. Kelner;David Steurer

  • Polynomial-Time Tensor Decompositions with Sum-of-Squares

    Tengyu Ma;Jonathan Shi;David Steurer

Frequent Co-Authors

Boaz Barak
Boaz Barak Harvard University
Prasad Raghavendra
Prasad Raghavendra University of California, Berkeley
Sanjeev Arora
Sanjeev Arora Princeton University
Irit Dinur
Irit Dinur Weizmann Institute of Science
Moritz Hardt
Moritz Hardt Max Planck Institute for Intelligent Systems
James R. Lee
James R. Lee University of Washington
Oded Regev
Oded Regev Courant Institute of Mathematical Sciences
Benjamin Doerr
Benjamin Doerr École Polytechnique
Peter Sanders
Peter Sanders Karlsruhe Institute of Technology
Johan Håstad
Johan Håstad Royal Institute of Technology

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