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Martín Abadi

At Google since November 2014, Google

  • At Google since November 2014, Google1
  • Emeritus, UC Santa Cruz12

Martín Abadi has been at Google since November 2014, according to Google's research profile, and is emeritus at UC Santa Cruz. Abadi is the first author of the TensorFlow white paper, which describes the system built at Google and its open-source release under the Apache 2.0 license, and of the 2016 paper TensorFlow: A system for large-scale machine learning. Abadi is also first author of Deep Learning with Differential Privacy (2016), which develops techniques for training deep neural networks under a modest privacy budget.12345

At a glance

Current roles
At Google since November 2014 +1 more
Sector
Company
Education
Stanford
Work listed
3
Honors
1
Sources cited
8
Profile reviewed

Security and programming languages

Abadi's publication record goes back to 1985 and spans algorithms and theory, security, and privacy. With Michael Burrows and Roger Needham, Abadi wrote A Logic of Authentication (1990), which gave systems designers a logic-based notation for describing and reasoning about authentication protocols; ACM SIGOPS added it to its Hall of Fame in 2007.16

Abadi's work on programming languages for security includes the applied pi calculus, an extension of the pi calculus for modeling cryptographic protocols, first introduced in a 2001 conference paper and later presented in full with Bruno Blanchet and Cedric Fournet in the Journal of the ACM (2017).1

Machine learning systems and privacy

After joining Google in November 2014, Abadi was first author of the March 2016 TensorFlow white paper and of the May 2016 paper TensorFlow: A system for large-scale machine learning. Abadi later co-authored work on dynamic control flow in TensorFlow and co-wrote an introduction to a computational model of TensorFlow that describes an operational semantics for its programs.1347

On privacy in machine learning, Abadi was first author of Deep Learning with Differential Privacy (2016) and co-authored the PATE approach, Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data, at ICLR 2017.581

Work and contributions

  • TensorFlow Open-source code

    First author of the TensorFlow white paper and of the 2016 paper TensorFlow: A system for large-scale machine learning; the white paper describes the interface and implementation built at Google and their open-source release under the Apache 2.0 license.341

  • Deep learning with differential privacy Published research

    First author of the 2016 paper that develops algorithmic techniques and a refined analysis of privacy costs for training deep neural networks within the framework of differential privacy.5

  • A Logic of Authentication Published research

    Co-author, with Michael Burrows and Roger Needham, of the 1990 paper that introduced a logic for reasoning about authentication protocols, inducted into the ACM SIGOPS Hall of Fame in 2007.6

Timeline

  1. Published A Logic of Authentication with Michael Burrows and Roger Needham in ACM Transactions on Computer Systems.6
  2. A Logic of Authentication was inducted into the ACM SIGOPS Hall of Fame.6
  3. Joined Google.1
  4. Posted the TensorFlow white paper on large-scale machine learning on heterogeneous distributed systems.3
  5. Posted TensorFlow, a system for large-scale machine learning, as first author.4
  6. Posted Deep Learning with Differential Privacy as first author.5
  7. Co-authored the PATE paper on knowledge transfer from private training data.8
  8. Co-authored Dynamic Control Flow in Large-Scale Machine Learning, on control flow in TensorFlow.7

Honors and recognition

  • ACM SIGOPS Hall of Fame Award (A Logic of Authentication) · ACM Special Interest Group on Operating Systems, 20076

Where they work

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References

8 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026

  1. Martín Abadi — Google Research profileGoogle Research · Official page · accessed Oct 21, 2026
  2. Martin Abadi — UC Santa Cruz home pageMartín Abadi (UC Santa Cruz) · Official page · accessed Oct 13, 2026
  3. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (arXiv 1603.04467)arXiv · Paper · published Mar 14, 2016 · accessed Oct 21, 2026
  4. TensorFlow: A system for large-scale machine learning (arXiv 1605.08695)arXiv · Paper · published May 27, 2016 · accessed Oct 21, 2026
  5. Deep Learning with Differential Privacy (arXiv 1607.00133)arXiv · Paper · published Jul 1, 2016 · accessed Oct 21, 2026
  6. ACM SIGOPS Hall of Fame AwardACM SIGOPS · Official page · accessed Oct 21, 2026
  7. Dynamic Control Flow in Large-Scale Machine Learning (arXiv 1805.01772)arXiv · Paper · published May 4, 2018 · accessed Oct 21, 2026
  8. Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (arXiv 1610.05755)arXiv · Paper · published Oct 18, 2016 · accessed Oct 21, 2026