World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
68
Citations
193014
World Ranking
2013
National Ranking
1015

Overview

Ian Goodfellow is affiliated with Google in the United States and focuses primarily on research within Computer Science. Their work spans several subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Hardware and Architecture, and Media Technology.

The main topics covered in their research include:

  • Generative Adversarial Networks and Image Synthesis
  • Computational Physics and Python Applications
  • Machine Learning and Algorithms
  • Adversarial Robustness in Machine Learning
  • Explainable Artificial Intelligence (XAI)
  • Machine Learning and Data Classification
  • Digital Media Forensic Detection

Goodfellow has contributed frequently to the following publication venues:

  • arXiv (Cornell University)
  • Nature Communications
  • Communications of the ACM

Among their recent papers are:

  • Generative adversarial networks (2020), Communications of the ACM
  • Static Analysis of Shape in TensorFlow Programs (2020), arXiv (Cornell University)
  • Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming (2020), arXiv (Cornell University)
  • Subtle adversarial image manipulations influence both human and machine perception (2023), Nature Communications
  • Creating High Resolution Images with a Latent Adversarial Generator (2020), arXiv (Cornell University)

Their frequent co-authors include:

  • Shreya Shankar
  • Alexey Kurakin
  • Mehdi Mirza
  • Aaron Courville
  • Yoshua Bengio

Best Publications

  • Generative Adversarial Nets

    Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu

  • Deep Learning

    Ian Goodfellow;Yoshua Bengio;Aaron Courville

  • Generative adversarial networks

    Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu

  • Explaining and Harnessing Adversarial Examples

    Ian J. Goodfellow;Jonathon Shlens;Christian Szegedy

  • Intriguing properties of neural networks

    Christian Szegedy;Wojciech Zaremba;Ilya Sutskever;Joan Bruna

  • TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

    Martín Abadi;Ashish Agarwal;Paul Barham;Eugene Brevdo

  • Improved techniques for training GANs

    Tim Salimans;Ian Goodfellow;Wojciech Zaremba;Vicki Cheung

  • Deep Learning with Differential Privacy

    Martin Abadi;Andy Chu;Ian Goodfellow;H. Brendan McMahan

  • Adversarial examples in the physical world

    Alexey Kurakin;Ian J. Goodfellow;Samy Bengio

  • Practical Black-Box Attacks against Machine Learning

    Nicolas Papernot;Patrick McDaniel;Ian Goodfellow;Somesh Jha

  • Self-Attention Generative Adversarial Networks

    Han Zhang;Ian J. Goodfellow;Dimitris N. Metaxas;Augustus Odena

  • Ensemble Adversarial Training: Attacks and Defenses

    Florian Tramèr;Alexey Kurakin;Nicolas Papernot;Ian J. Goodfellow

  • Maxout Networks

    Ian Goodfellow;David Warde-Farley;Mehdi Mirza;Aaron Courville

  • Adversarial Machine Learning at Scale

    Alexey Kurakin;Ian J. Goodfellow;Samy Bengio

  • Theano: A Python framework for fast computation of mathematical expressions

    Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

  • MixMatch: A Holistic Approach to Semi-Supervised Learning

    David Berthelot;Nicholas Carlini;Ian Goodfellow;Nicolas Papernot

  • Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

    Nicolas Papernot;Patrick D. McDaniel;Ian J. Goodfellow

  • Challenges in Representation Learning: A Report on Three Machine Learning Contests

    Ian J. Goodfellow;Dumitru Erhan;Pierre Luc Carrier;Aaron Courville

  • Theano: new features and speed improvements

    Frédéric Bastien;Pascal Lamblin;Razvan Pascanu;James Bergstra

  • NIPS 2016 Tutorial: Generative Adversarial Networks

    Ian J. Goodfellow

  • Sanity Checks for Saliency Maps

    Julius Adebayo;Justin Gilmer;Michael Christoph Muelly;Ian Goodfellow

Frequent Co-Authors

Yoshua Bengio
Yoshua Bengio University of Montreal
Aaron Courville
Aaron Courville University of Montreal
Nicolas Papernot
Nicolas Papernot University of Toronto
Colin Raffel
Colin Raffel University of Toronto
Patrick McDaniel
Patrick McDaniel University of Wisconsin–Madison
Jonathon Shlens
Jonathon Shlens Google (United States)
Nicholas Carlini
Nicholas Carlini Google (United States)
Martín Abadi
Martín Abadi Google (United States)
Samy Bengio
Samy Bengio Apple (United States)
Kunal Talwar
Kunal Talwar Apple (United States)

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