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
- Companies
- Google, UC Santa Cruz
- 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
- Published A Logic of Authentication with Michael Burrows and Roger Needham in ACM Transactions on Computer Systems.6
- A Logic of Authentication was inducted into the ACM SIGOPS Hall of Fame.6
- Joined Google.1
- Posted the TensorFlow white paper on large-scale machine learning on heterogeneous distributed systems.3
- Posted TensorFlow, a system for large-scale machine learning, as first author.4
- Posted Deep Learning with Differential Privacy as first author.5
- Co-authored the PATE paper on knowledge transfer from private training data.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
- Google 121 people in the wiki
- UC Santa Cruz 1 person in the wiki
Related people
- Jeff DeanAlso at Google
- Fabian PedregosaAlso at Google
- Adam PaszkeAlso at Google
- Alex SmolaAlso at Google
- Cho-Jui HsiehAlso at Google
- Luca AntigaML frameworks and libraries · Training systems
- Roy FrostigML frameworks and libraries · Machine-learning theory
- Pieter NoordhuisTraining systems · ML frameworks and libraries
- Edward YangML frameworks and libraries · Training systems
- Clément FarabetTraining systems · ML frameworks and libraries
Suggest a correction or removal
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References
8 sources · profile reviewed Oct 21, 2026 · data updated Oct 21, 2026
- Martín Abadi — Google Research profile
- Martin Abadi — UC Santa Cruz home page
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (arXiv 1603.04467)
- TensorFlow: A system for large-scale machine learning (arXiv 1605.08695)
- Deep Learning with Differential Privacy (arXiv 1607.00133)
- ACM SIGOPS Hall of Fame Award
- Dynamic Control Flow in Large-Scale Machine Learning (arXiv 1805.01772)
- Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (arXiv 1610.05755)