World's Best Scientists 2026 revealed!

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Computer Science

D-Index
44
Citations
15389
World Ranking
7386
National Ranking
97

Overview

Reza Shokri is affiliated with the National University of Singapore in Singapore and has contributed extensively to the field of computer science, with a primary focus on artificial intelligence. Their research spans over 70 publications in computer science, including 65 in artificial intelligence and subfields such as safety research, sociology and political science, computer networks and communications, and health informatics.

Their main research topics include:

  • Privacy-Preserving Technologies in Data
  • Adversarial Robustness in Machine Learning
  • Stochastic Gradient Optimization Techniques
  • Ethics and Social Impacts of AI
  • Topic Modeling
  • Cryptography and Data Security
  • Explainable Artificial Intelligence (XAI)

Reza Shokri has published numerous papers in a variety of venues, with many contributions to arXiv (Cornell University) totaling 29 publications. Other frequent publication venues include the Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, the 2022 ACM Conference on Fairness, Accountability, and Transparency, IEEE Security & Privacy, and Sensors.

Recent notable papers include:

  • "Enhanced Membership Inference Attacks against Machine Learning Models," 2022, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
  • "What Does it Mean for a Language Model to Preserve Privacy?" 2022, 2022 ACM Conference on Fairness, Accountability, and Transparency
  • "Epione: Lightweight Contact Tracing with Strong Privacy," 2020, arXiv (Cornell University)
  • "Truth Serum," 2022, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
  • "ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning," 2020, arXiv (Cornell University)

The scientist frequently collaborates with other researchers such as Jiayuan Ye, Hongyan Chang, Sasi Kumar Murakonda, Fatemehsadat Mireshghallah, and Florian Tramèr. These coauthors have contributed multiple joint publications, with Jiayuan Ye being the most frequent coauthor.

Best Publications

  • Membership Inference Attacks Against Machine Learning Models

    Reza Shokri;Marco Stronati;Congzheng Song;Vitaly Shmatikov

  • Privacy-Preserving Deep Learning

    Reza Shokri;Vitaly Shmatikov

  • Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

    Milad Nasr;Reza Shokri;Amir Houmansadr

  • Quantifying Location Privacy

    Reza Shokri;George Theodorakopoulos;Jean-Yves Le Boudec;Jean-Pierre Hubaux

  • Protecting location privacy: optimal strategy against localization attacks

    Reza Shokri;George Theodorakopoulos;Carmela Troncoso;Jean-Pierre Hubaux

  • Machine Learning with Membership Privacy using Adversarial Regularization

    Milad Nasr;Reza Shokri;Amir Houmansadr

  • Privacy Risks of Securing Machine Learning Models against Adversarial Examples

    Liwei Song;Reza Shokri;Prateek Mittal

  • On the Optimal Placement of Mix Zones

    Julien Freudiger;Reza Shokri;Jean-Pierre Hubaux

  • Enhanced Membership Inference Attacks against Machine Learning Models

    Unknown

  • Hiding in the Mobile Crowd: LocationPrivacy through Collaboration

    Reza Shokri;George Theodorakopoulos;Panos Papadimitratos;Ehsan Kazemi

  • Privacy-preserving deep learning

    Reza Shokri;Vitaly Shmatikov

  • Synthesizing Plausible Privacy-Preserving Location Traces

    Vincent Bindschaedler;Reza Shokri

  • What Does it Mean for a Language Model to Preserve Privacy?

    Unknown

  • Evaluating the privacy risk of location-based services

    Julien Freudiger;Reza Shokri;Jean-Pierre Hubaux

  • Chiron: Privacy-preserving Machine Learning as a Service.

    Tyler Hunt;Congzheng Song;Reza Shokri;Vitaly Shmatikov

  • Unraveling an old cloak: k-anonymity for location privacy

    Reza Shokri;Carmela Troncoso;Claudia Diaz;Julien Freudiger

  • Privacy Games: Optimal User-Centric Data Obfuscation

    Reza Shokri

  • Quantifying location privacy: the case of sporadic location exposure

    Reza Shokri;George Theodorakopoulos;George Danezis;Jean-Pierre Hubaux

  • Plausible deniability for privacy-preserving data synthesis

    Vincent Bindschaedler;Reza Shokri;Carl A. Gunter

  • Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks.

    Milad Nasr;Reza Shokri;Amir Houmansadr

  • A distortion-based metric for location privacy

    Reza Shokri;Julien Freudiger;Murtuza Jadliwala;Jean-Pierre Hubaux

  • Defeating Image Obfuscation with Deep Learning

    Richard McPherson;Reza Shokri;Vitaly Shmatikov

  • Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer.

    Hongyan Chang;Virat Shejwalkar;Reza Shokri;Amir Houmansadr

Frequent Co-Authors

Jean-Pierre Hubaux
Jean-Pierre Hubaux École Polytechnique Fédérale de Lausanne
Amir Houmansadr
Amir Houmansadr University of Massachusetts Amherst
Vitaly Shmatikov
Vitaly Shmatikov Cornell University
Panos Papadimitratos
Panos Papadimitratos Royal Institute of Technology
Jean-Yves Le Boudec
Jean-Yves Le Boudec École Polytechnique Fédérale de Lausanne
Prateek Mittal
Prateek Mittal Princeton University
George Danezis
George Danezis University College London
Carl A. Gunter
Carl A. Gunter University of Illinois at Urbana-Champaign
Prateek Saxena
Prateek Saxena National University of Singapore
Dawn Song
Dawn Song University of California, Berkeley

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