World's Best Scientists 2026 revealed!
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Mathematics
USA
2026

D-Index & Metrics

Computer Science

D-Index
86
Citations
54351
World Ranking
748
National Ranking
395

Mathematics

D-Index
80
Citations
49760
World Ranking
139
National Ranking
79

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2012 - Fellow of Alfred P. Sloan Foundation

Overview

Benjamin Recht is affiliated with the University of California, Berkeley in the United States. Their research spans multiple fields within computer science and engineering, focusing extensively on artificial intelligence and control systems.

The main fields of study for Benjamin Recht include:

  • Computer Science
  • Engineering

Their work further explores specialized subfields such as:

  • Artificial Intelligence
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • Media Technology

Benjamin Recht's research topics include:

  • Stochastic Gradient Optimization Techniques
  • Control Systems and Identification
  • Advanced Control Systems Optimization
  • Fault Detection and Control Systems
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Advanced Vision and Imaging

Recent notable papers authored or co-authored by Benjamin Recht comprise:

  • "Understanding deep learning (still) requires rethinking generalization," 2021, Communications of the ACM
  • "Plenoxels: Radiance Fields without Neural Networks," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Measuring Robustness to Natural Distribution Shifts in Image Classification," 2020, arXiv (Cornell University)
  • "A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery," 2020, arXiv (Cornell University)
  • "Neural Kernels Without Tangents," 2020, arXiv (Cornell University)

Frequent co-authors working alongside Benjamin Recht include:

  • Stephen J. Wright
  • Sara Fridovich-Keil
  • Esther Rolf
  • Sarah Dean

Benjamin Recht has been published frequently in venues such as:

  • arXiv (Cornell University)
  • Cambridge University Press eBooks
  • Communications of the ACM
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 60th IEEE Conference on Decision and Control (CDC)

In recognition of their contributions, Benjamin Recht was named a Fellow of the Alfred P. Sloan Foundation in 2012.

Best Publications

  • Exact matrix completion via convex optimization

    Emmanuel Candès;Benjamin Recht

  • Understanding deep learning (still) requires rethinking generalization

    Chiyuan Zhang;Samy Bengio;Moritz Hardt;Benjamin Recht

  • Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization

    Benjamin Recht;Maryam Fazel;Pablo A. Parrilo

  • Random Features for Large-Scale Kernel Machines

    Ali Rahimi;Benjamin Recht

  • Understanding deep learning requires rethinking generalization.

    Chiyuan Zhang;Samy Bengio;Moritz Hardt;Benjamin Recht

  • Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

    Benjamin Recht;Christopher Re;Stephen Wright;Feng Niu

  • HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

    Feng Niu;Benjamin Recht;Christopher Re;Stephen J. Wright

  • Plenoxels: Radiance Fields without Neural Networks

    Unknown

  • The Convex Geometry of Linear Inverse Problems

    Venkat Chandrasekaran;Benjamin Recht;Pablo A. Parrilo;Alan S. Willsky

  • Compressed Sensing Off the Grid

    Gongguo Tang;Badri Narayan Bhaskar;Parikshit Shah;Benjamin Recht

  • A Simpler Approach to Matrix Completion

    Benjamin Recht

  • The Marginal Value of Adaptive Gradient Methods in Machine Learning

    Ashia C. Wilson;Rebecca Roelofs;Mitchell Stern;Nathan Srebro

  • Tensor completion and low-n-rank tensor recovery via convex optimization

    Silvia Gandy;Benjamin Recht;Isao Yamada

  • Train faster, generalize better: stability of stochastic gradient descent

    Moritz Hardt;Benjamin Recht;Yoram Singer

  • Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints

    Laurent Lessard;Benjamin Recht;Andrew K. Packard

  • Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning

    Ali Rahimi;Benjamin Recht

  • Atomic Norm Denoising With Applications to Line Spectral Estimation

    Badri Narayan Bhaskar;Gongguo Tang;Benjamin Recht

  • Do ImageNet Classifiers Generalize to ImageNet

    Benjamin Recht;Rebecca Roelofs;Ludwig Schmidt;Vaishaal Shankar

  • A Tour of Reinforcement Learning: The View from Continuous Control

    Benjamin Recht

  • Gradient descent only converges to minimizers

    Jason D. Lee;Max Simchowitz;Michael I. Jordan;Benjamin Recht

  • On the Sample Complexity of the Linear Quadratic Regulator

    Sarah Dean;Horia Mania;Nikolai Matni;Benjamin Recht

Frequent Co-Authors

Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Christopher Ré
Christopher Ré Stanford University
Moritz Hardt
Moritz Hardt Max Planck Institute for Intelligent Systems
Robert Nowak
Robert Nowak University of Wisconsin–Madison
Shivaram Venkataraman
Shivaram Venkataraman University of Wisconsin–Madison
Emmanuel J. Candès
Emmanuel J. Candès Stanford University
Kannan Ramchandran
Kannan Ramchandran University of California, Berkeley
Mahdi Soltanolkotabi
Mahdi Soltanolkotabi University of Southern California
Andrew Packard
Andrew Packard University of California, Berkeley
Jason D. Lee
Jason D. Lee Princeton University

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