World's Best Scientists 2026 revealed!
Alex Beutel

Alex Beutel

D-Index & Metrics

Computer Science

D-Index
35
Citations
6051
World Ranking
11599
National Ranking
4761

Overview

Alex Beutel is affiliated with OpenAI in the United States and has an extensive research record in computer science, particularly within artificial intelligence. Their work predominantly appears in the venue arXiv (Cornell University), with 30 publications, alongside contributions to conferences and journals such as the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, IEEE Journal on Selected Areas in Information Theory, and Dagstuhl Research Online Publication Server.

Their research spans several subfields, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • Safety Research
  • Information Systems

Within these areas, the main topics explored include:

  • Adversarial Robustness in Machine Learning
  • Explainable Artificial Intelligence (XAI)
  • Topic Modeling
  • Natural Language Processing Techniques
  • Ethics and Social Impacts of AI
  • Recommender Systems and Techniques
  • Multimodal Machine Learning Applications

Among the recent papers published by Alex Beutel are:

  • "Underspecification Presents Challenges for Credibility in Modern Machine Learning," 2020, arXiv (Cornell University)
  • "Measuring and Reducing Gendered Correlations in Pre-trained Models," 2020, arXiv (Cornell University)
  • "GPT-4o System Card," 2024, arXiv (Cornell University)
  • "Fairness without Demographics through Adversarially Reweighted Learning," 2020, arXiv (Cornell University)
  • "Measuring Recommender System Effects with Simulated Users," 2021, arXiv (Cornell University)

Frequent collaborators in their research include:

  • Jilin Chen
  • Xuezhi Wang
  • Ed H.
  • Ahmad Beirami
  • Ben Packer

Best Publications

  • The Case for Learned Index Structures

    Tim Kraska;Alex Beutel;Ed H. Chi;Jeffrey Dean

  • Recurrent Recommender Networks

    Chao-Yuan Wu;Amr Ahmed;Alex Beutel;Alexander J. Smola

  • Underspecification Presents Challenges for Credibility in Modern Machine Learning

    Alexander D'Amour;Katherine A. Heller;Dan Moldovan;Ben Adlam

  • CopyCatch: stopping group attacks by spotting lockstep behavior in social networks

    Alex Beutel;Wanhong Xu;Venkatesan Guruswami;Christopher Palow

  • Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

    Alex Beutel;Ed H. Chi;Jilin Chen;Zhe Zhao

  • Top-K Off-Policy Correction for a REINFORCE Recommender System

    Minmin Chen;Alex Beutel;Paul Covington;Sagar Jain

  • FRAUDAR: Bounding Graph Fraud in the Face of Camouflage

    Bryan Hooi;Hyun Ah Song;Alex Beutel;Neil Shah

  • Latent Cross: Making Use of Context in Recurrent Recommender Systems

    Alex Beutel;Paul Covington;Sagar Jain;Can Xu

  • Fairness in Recommendation Ranking through Pairwise Comparisons

    Alex Beutel;Jilin Chen;Tulsee Doshi;Hai Qian

  • CatchSync: catching synchronized behavior in large directed graphs

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • Counterfactual Fairness in Text Classification through Robustness

    Sahaj Garg;Vincent Perot;Nicole Limtiaco;Ankur Taly

  • Winner takes all: competing viruses or ideas on fair-play networks

    B. Aditya Prakash;Alex Beutel;Roni Rosenfeld;Christos Faloutsos

  • Interacting viruses in networks: can both survive?

    Alex Beutel;B. Aditya Prakash;Roni Rosenfeld;Christos Faloutsos

  • Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements

    Alex Beutel;Jilin Chen;Tulsee Doshi;Hai Qian

  • FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop

    Alex Beutel;Partha Pratim Talukdar;Abhimanu Kumar;Christos Faloutsos

  • SageDB: A Learned Database System

    Tim Kraska;Mohammad Alizadeh;Alex Beutel;Ed H. Chi

  • BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.

    Bryan Hooi;Neil Shah;Alex Beutel;Stephan Günnemann

  • Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective

    Neil Shah;Alex Beutel;Brian Gallagher;Christos Faloutsos

  • Measuring and Reducing Gendered Correlations in Pre-trained Models

    Kellie Webster;Xuezhi Wang;Ian Tenney;Alex Beutel

  • Q&R: A Two-Stage Approach toward Interactive Recommendation

    Konstantina Christakopoulou;Alex Beutel;Rui Li;Sagar Jain

  • Inferring Strange Behavior from Connectivity Pattern in Social Networks

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • A General Suspiciousness Metric for Dense Blocks in Multimodal Data

    Meng Jiang;Alex Beutel;Peng Cui;Bryan Hooi

  • Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach

    Meng Jiang;Peng Cui;Alex Beutel;Christos Faloutsos

  • Beyond Globally Optimal: Focused Learning for Improved Recommendations

    Alex Beutel;Ed H. Chi;Zhiyuan Cheng;Hubert Pham

  • Network Anomaly Detection Using Co-clustering

    E. E. Papalexakis;A. Beutel;P. Steenkiste

  • Graph-Based Fraud Detection in the Face of Camouflage

    Bryan Hooi;Kijung Shin;Hyun Ah Song;Alex Beutel

Frequent Co-Authors

Ed H. Chi
Ed H. Chi Google (United States)
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Stephan Günnemann
Stephan Günnemann Technical University of Munich
Amr Ahmed
Amr Ahmed University of Nottingham Malaysia Campus
Leman Akoglu
Leman Akoglu Carnegie Mellon University
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Craig Boutilier
Craig Boutilier Google (United States)
Lichan Hong
Lichan Hong Google (United States)

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