World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
86
Citations
29258
World Ranking
771
National Ranking
413

Research.com Recognitions

  • 2015 - Fellow of the MacArthur Foundation
  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Christopher Ré is affiliated with Stanford University in the United States. Their research primarily focuses on the domain of Computer Science, with a notable emphasis on Artificial Intelligence and related interdisciplinary areas.

Their work spans several subfields of study, which include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Molecular Biology
  • Management Science and Operations Research

Major topics covered across their publications are:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Machine Learning and Data Classification
  • Multimodal Machine Learning Applications
  • Advanced Graph Neural Networks

Christopher Ré has published extensively in research venues such as:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Communications of the ACM
  • Findings of the Association for Computational Linguistics: ACL 2022
  • Zenodo (CERN European Organization for Nuclear Research)

Frequent collaborators include:

  • Daniel Y. Fu
  • Tri Dao
  • Atri Rudra
  • Simran Arora
  • Avanika Narayan

Representative recent papers highlight topics related to foundation models, attention mechanisms, and sequence modeling. Some of these are:

  • On the Opportunities and Risks of Foundation Models (2021), arXiv (Cornell University)
  • Efficiently Modeling Long Sequences with Structured State Spaces (2021), arXiv (Cornell University)
  • FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness (2022), arXiv (Cornell University)
  • HiPPO: Recurrent Memory with Optimal Polynomial Projections (2020), arXiv (Cornell University)
  • Hungry Hungry Hippos: Towards Language Modeling with State Space Models (2022), arXiv (Cornell University)

Christopher Ré has been recognized by major awards, specifically:

  • Fellow of the MacArthur Foundation, 2015
  • Fellow of Alfred P. Sloan Foundation, 2013

Best Publications

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

    Benjamin Recht;Christopher Re;Stephen Wright;Feng Niu

  • On the Opportunities and Risks of Foundation Models.

    Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

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

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

  • Snorkel: rapid training data creation with weak supervision

    Alexander Ratner;Stephen H. Bach;Henry Ehrenberg;Jason Fries

  • Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features.

    Kun-Hsing Yu;Ce Zhang;Gerald J. Berry;Russ B. Altman

  • Data Programming: Creating Large Training Sets, Quickly

    Alexander J. Ratner;Christopher M. De Sa;Sen Wu;Daniel Selsam

  • HoloClean: holistic data repairs with probabilistic inference

    Theodoros Rekatsinas;Xu Chu;Ihab F. Ilyas;Christopher Ré

  • The MADlib analytics library: or MAD skills, the SQL

    Joseph M. Hellerstein;Christoper Ré;Florian Schoppmann;Daisy Zhe Wang

  • Efficient Top-k Query Evaluation on Probabilistic Data

    C. Re;N. Dalvi;D. Suciu

  • Efficiently Modeling Long Sequences with Structured State Spaces

    Albert Gu;Karan Goel;Christopher Ré

  • Hyperbolic Graph Convolutional Neural Networks.

    Ines Chami;Rex Ying;Christopher Ré;Jure Leskovec

  • Parallel stochastic gradient algorithms for large-scale matrix completion

    Benjamin Recht;Christopher Ré

  • An asynchronous parallel stochastic coordinate descent algorithm

    Ji Liu;Stephen J. Wright;Christopher Ré;Victor Bittorf

  • Learning to Compose Domain-Specific Transformations for Data Augmentation.

    Alexander J Ratner;Henry R Ehrenberg;Zeshan Hussain;Jared Dunnmon

  • Hidden stratification causes clinically meaningful failures in machine learning for medical imaging

    Luke Oakden-Rayner;Jared Dunnmon;Gustavo Carneiro;Christopher Re

  • Low-Dimensional Hyperbolic Knowledge Graph Embeddings

    Ines Chami;Adva Wolf;Da-Cheng Juan;Frederic Sala

  • Using Social Media to Measure Labor Market Flows

    Dolan Antenucci;Michael Cafarella;Margaret Levenstein;Christopher Ré

  • Representation Tradeoffs for Hyperbolic Embeddings.

    Christopher De Sa;Albert Gu;Christopher Ré;Frederic Sala

  • Incremental knowledge base construction using DeepDive

    Jaeho Shin;Sen Wu;Feiran Wang;Christopher De Sa

  • Event queries on correlated probabilistic streams

    Christopher Ré;Julie Letchner;Magdalena Balazinksa;Dan Suciu

  • MYSTIQ: a system for finding more answers by using probabilities

    Jihad Boulos;Nilesh Dalvi;Bhushan Mandhani;Shobhit Mathur

  • Probabilistic databases: diamonds in the dirt

    Nilesh Dalvi;Christopher Ré;Dan Suciu

  • HiPPO: Recurrent Memory with Optimal Polynomial Projections

    Albert Gu;Tri Dao;Stefano Ermon;Atri Rudra

Frequent Co-Authors

Ce Zhang
Ce Zhang ETH Zurich
Dan Suciu
Dan Suciu University of Washington
Atri Rudra
Atri Rudra University at Buffalo, State University of New York
Kunle Olukotun
Kunle Olukotun Stanford University
Hung Q. Ngo
Hung Q. Ngo University at Buffalo, State University of New York
Daniel L. Rubin
Daniel L. Rubin Stanford University
Benjamin Recht
Benjamin Recht University of California, Berkeley
Magdalena Balazinska
Magdalena Balazinska University of Washington
Michael Snyder
Michael Snyder Stanford University

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