2026 Reza Shokri: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	44	7386	7169	97	97	83	15389

Reza Shokri publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Reza Shokri sits on this spectrum.

32 publications 991+

This scientist: 83 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Reza Shokri D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Reza Shokri sits on this spectrum.

30 D-Index 131+

This scientist: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

4057
Citations
Privacy-Preserving Deep Learning

Reza Shokri;Vitaly Shmatikov

2329
Citations
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Milad Nasr;Reza Shokri;Amir Houmansadr

1563
Citations
Quantifying Location Privacy

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

908
Citations
Protecting location privacy: optimal strategy against localization attacks

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

497
Citations
Machine Learning with Membership Privacy using Adversarial Regularization

Milad Nasr;Reza Shokri;Amir Houmansadr

440
Citations
Privacy Risks of Securing Machine Learning Models against Adversarial Examples

Liwei Song;Reza Shokri;Prateek Mittal

324
Citations
On the Optimal Placement of Mix Zones

Julien Freudiger;Reza Shokri;Jean-Pierre Hubaux

246
Citations
Enhanced Membership Inference Attacks against Machine Learning Models

Unknown

242
Citations
Hiding in the Mobile Crowd: LocationPrivacy through Collaboration

Reza Shokri;George Theodorakopoulos;Panos Papadimitratos;Ehsan Kazemi

241
Citations
Privacy-preserving deep learning

Reza Shokri;Vitaly Shmatikov

236
Citations
Synthesizing Plausible Privacy-Preserving Location Traces

Vincent Bindschaedler;Reza Shokri

230
Citations
What Does it Mean for a Language Model to Preserve Privacy?

Unknown

212
Citations
Evaluating the privacy risk of location-based services

Julien Freudiger;Reza Shokri;Jean-Pierre Hubaux

209
Citations
Chiron: Privacy-preserving Machine Learning as a Service.

Tyler Hunt;Congzheng Song;Reza Shokri;Vitaly Shmatikov

193
Citations
Unraveling an old cloak: k-anonymity for location privacy

Reza Shokri;Carmela Troncoso;Claudia Diaz;Julien Freudiger

189
Citations
Privacy Games: Optimal User-Centric Data Obfuscation

Reza Shokri

185
Citations
Quantifying location privacy: the case of sporadic location exposure

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

164
Citations
Plausible deniability for privacy-preserving data synthesis

Vincent Bindschaedler;Reza Shokri;Carl A. Gunter

160
Citations
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

158
Citations
A distortion-based metric for location privacy

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

153
Citations
Defeating Image Obfuscation with Deep Learning

Richard McPherson;Reza Shokri;Vitaly Shmatikov

131
Citations
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer.

Hongyan Chang;Virat Shejwalkar;Reza Shokri;Amir Houmansadr

87
Citations

Frequent Co-Authors

Jean-Pierre Hubaux École Polytechnique Fédérale de Lausanne

Amir Houmansadr University of Massachusetts Amherst

Vitaly Shmatikov Cornell University

Panos Papadimitratos Royal Institute of Technology

Jean-Yves Le Boudec École Polytechnique Fédérale de Lausanne

Prateek Mittal Princeton University

George Danezis University College London

Carl A. Gunter University of Illinois at Urbana-Champaign

Prateek Saxena National University of Singapore

Dawn Song University of California, Berkeley

External Links

Personal website of Reza Shokri Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring online degrees offers flexibility and can lead to lucrative opportunities in tech. If you’re seeking a fast track to a rewarding job, consider looking into the easiest online degrees that pay well. These programs are designed for efficiency without compromising future earning potential.

Artificial intelligence continues to be a booming field. Those interested in future-proof careers should review the ai degrees that combine affordability with high demand skills. These degrees can lead to roles in automation, data science, and tech development.

For broader guidance on smart education choices, check out the top degrees for the future. This resource outlines majors most likely to deliver strong employment growth and higher salaries, helping students plan for long-term success.

If continuing your education is a priority, you might want to investigate what's the easiest masters degree to get. Completing an accessible yet valuable master’s program can further boost your qualifications and open up more career pathways.