World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
21746
World Ranking
3005
National Ranking
1473

Overview

Joseph E. Gonzalez is affiliated with the University of California, Berkeley in the United States. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Control and Systems Engineering, and Information Systems.

Their scholarly work covers a range of main topics, reflecting diverse interests within computer science. These topics include:

  • Multimodal Machine Learning Applications
  • Topic Modeling
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Natural Language Processing Techniques
  • Reinforcement Learning in Robotics
  • Robot Manipulation and Learning

Joseph E. Gonzalez has contributed to numerous publications, predominantly appearing in the venue arXiv (Cornell University) with 145 publications. Other frequent publication venues include Proceedings of the VLDB Endowment, IEEE Robotics and Automation Letters, the 2021 IEEE/CVF International Conference on Computer Vision (ICCV), and IEEE Transactions on Neural Networks and Learning Systems.

Recent papers authored or co-authored include:

  • "Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena" (2023), published in arXiv (Cornell University)
  • "A Review of Single-Source Deep Unsupervised Visual Domain Adaptation" (2020), published in IEEE Transactions on Neural Networks and Learning Systems
  • "The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink" (2022), published in Computer
  • "Cloudburst" (2020), published in Proceedings of the VLDB Endowment
  • "What serverless computing is and should become" (2021), published in Communications of the ACM

The scientist has collaborated frequently with several co-authors, including:

  • Ion Stoica, with 60 joint publications
  • Ken Goldberg, with 25 joint publications
  • Trevor Darrell, with 25 joint publications
  • Brijen Thananjeyan, with 19 joint publications
  • Tianjun Zhang, with 18 joint publications

Best Publications

  • Apache Spark: a unified engine for big data processing

    Matei Zaharia;Reynold S. Xin;Patrick Wendell;Tathagata Das

  • PowerGraph: distributed graph-parallel computation on natural graphs

    Joseph E. Gonzalez;Yucheng Low;Haijie Gu;Danny Bickson

  • Distributed GraphLab: a framework for machine learning and data mining in the cloud

    Yucheng Low;Danny Bickson;Joseph Gonzalez;Carlos Guestrin

  • GraphX: graph processing in a distributed dataflow framework

    Joseph E. Gonzalez;Reynold S. Xin;Ankur Dave;Daniel Crankshaw

  • GraphX: a resilient distributed graph system on Spark

    Reynold S. Xin;Joseph E. Gonzalez;Michael J. Franklin;Ion Stoica

  • Tune: A Research Platform for Distributed Model Selection and Training.

    Richard Liaw;Eric Liang;Robert Nishihara;Philipp Moritz

  • GraphLab: a new framework for parallel machine learning

    Yucheng Low;Joseph Gonzalez;Aapo Kyrola;Danny Bickson

  • SkipNet: Learning Dynamic Routing in Convolutional Networks

    Xin Wang;Fisher Yu;Zi-Yi Dou;Trevor Darrell

  • GraphLab: A New Parallel Framework for Machine Learning

    Yucheng Low;Joseph E. Gonzalez;Aapo Kyrola;Danny Bickson

  • Cloud Programming Simplified: A Berkeley View on Serverless Computing

    Eric Jonas;Johann Schleier-Smith;Vikram Sreekanti;Chia-che Tsai

  • Clipper: a low-latency online prediction serving system

    Daniel Crankshaw;Xin Wang;Giulio Zhou;Michael J. Franklin

  • Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions

    Bichen Wu;Alvin Wan;Xiangyu Yue;Peter Jin

  • Scalable inference in latent variable models

    Amr Ahmed;Moahmed Aly;Joseph Gonzalez;Shravan Narayanamurthy

  • Opaque: an oblivious and encrypted distributed analytics platform

    Wenting Zheng;Ankur Dave;Jethro G. Beekman;Raluca Ada Popa

  • Serverless Computing: One Step Forward, Two Steps Back.

    Joseph M. Hellerstein;Jose M. Faleiro;Joseph E. Gonzalez;Johann Schleier-Smith

  • FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

    Alvin Wan;Xiaoliang Dai;Peizhao Zhang;Zijian He

  • Frustratingly Simple Few-Shot Object Detection

    Xin Wang;Thomas Huang;Joseph Gonzalez;Trevor Darrell

  • RLlib: Abstractions for Distributed Reinforcement Learning

    Eric Liang;Richard Liaw;Philipp Moritz;Robert Nishihara

  • Distributed GraphLab: A Framework for Machine Learning in the Cloud

    Yucheng Low;Joseph Gonzalez;Aapo Kyrola;Danny Bickson

  • RLlib: Abstractions for Distributed Reinforcement Learning

    Eric Liang;Richard Liaw;Robert Nishihara;Philipp Moritz

  • Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning.

    Vladimir Feinberg;Alvin Wan;Ion Stoica;Michael I. Jordan

Frequent Co-Authors

Ion Stoica
Ion Stoica University of California, Berkeley
Ken Goldberg
Ken Goldberg University of California, Berkeley
Joseph M. Hellerstein
Joseph M. Hellerstein University of California, Berkeley
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Kurt Keutzer
Kurt Keutzer University of California, Berkeley
Carlos Guestrin
Carlos Guestrin Stanford University
Trevor Darrell
Trevor Darrell University of California, Berkeley
Fisher Yu
Fisher Yu ETH Zurich
Michael W. Mahoney
Michael W. Mahoney University of California, Berkeley
Michael J. Franklin
Michael J. Franklin University of Chicago

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