2026 Prateek Mittal: 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	53	4718	4586	2192	2115	201	16111

Prateek Mittal 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 Prateek Mittal sits on this spectrum.

32 publications 991+

This scientist: 201 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Prateek Mittal 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 Prateek Mittal sits on this spectrum.

30 D-Index 131+

This scientist: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

2017 - ACM Senior Member

Overview

Prateek Mittal is affiliated with Princeton University in the United States and has a research focus primarily in the field of Computer Science, with a significant number of publications totaling 178. Their work spans various subfields including Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition, and Hardware and Architecture.

The main topics covered in Mittal's research include:

Adversarial Robustness in Machine Learning
Privacy-Preserving Technologies in Data
Internet Traffic Analysis and Secure E-voting
Anomaly Detection Techniques and Applications
Advanced Malware Detection Techniques
Network Security and Intrusion Detection
Cryptography and Data Security

Mittal's recent scholarly outputs include the following papers:

Advances and Open Problems in Federated Learning, 2020, published in Foundations and Trends® in Machine Learning
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning, 2021, published in DOAJ (Directory of Open Access Journals)
RobustBench: a standardized adversarial robustness benchmark, 2020, published in arXiv (Cornell University)
Systematic Evaluation of Privacy Risks of Machine Learning Models, 2020, published in arXiv (Cornell University)
Visual Adversarial Examples Jailbreak Aligned Large Language Models, 2024, published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in Mittal's research include:

Vikash Sehwag
Saeed Mahloujifar
Chong Xiang
Ashwinee Panda
Jiachen T. Wang

The venues where Mittal has most commonly published are:

arXiv (Cornell University), with 67 publications
Proceedings on Privacy Enhancing Technologies, with 5 publications
Communications of the ACM, with 2 publications
Zenodo (CERN European Organization for Nuclear Research), with 2 publications
Foundations and Trends® in Machine Learning, with 1 publication

Mittal was awarded the ACM Senior Member distinction in 2017. The recognition highlights standing within the professional computing community.

Best Publications

Advances and Open Problems in Federated Learning

Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

4595
Citations
Advances and open problems in federated learning

Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

1189
Citations
SybilInfer: Detecting Sybil Nodes using Social Networks.

George Danezis;Prateek Mittal

605
Citations
EASiER: encryption-based access control in social networks with efficient revocation

Sonia Jahid;Prateek Mittal;Nikita Borisov

588
Citations
Analyzing Federated Learning through an Adversarial Lens

Arjun Nitin Bhagoji;Supriyo Chakraborty;Prateek Mittal;Seraphin B. Calo

551
Citations
BotGrep: finding P2P bots with structured graph analysis

Shishir Nagaraja;Prateek Mittal;Chi-Yao Hong;Matthew Caesar

331
Citations
Privacy Risks of Securing Machine Learning Models against Adversarial Examples

Liwei Song;Reza Shokri;Prateek Mittal

324
Citations
Evolution of social-attribute networks: measurements, modeling, and implications using google+

Neil Zhenqiang Gong;Wenchang Xu;Ling Huang;Prateek Mittal

263
Citations
BlackIoT: IoT botnet of high wattage devices can disrupt the power grid

Saleh Soltan;Prateek Mittal;H. Vincent Poor

258
Citations
DARTS: Deceiving Autonomous Cars with Toxic Signs

Chawin Sitawarin;Arjun Nitin Bhagoji;Arsalan Mosenia;Mung Chiang

244
Citations
SybilBelief: A Semi-Supervised Learning Approach for Structure-Based Sybil Detection

Neil Zhenqiang Gong;Mario Frank;Prateek Mittal

237
Citations
Enhancing robustness of machine learning systems via data transformations

Arjun Nitin Bhagoji;Daniel Cullina;Chawin Sitawarin;Prateek Mittal

232
Citations
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning

Sameer Wagh;Shruti Tople;Fabrice Benhamouda;Eyal Kushilevitz

226
Citations
Denial of service or denial of security

Nikita Borisov;George Danezis;Prateek Mittal;Parisa Tabriz

213
Citations
Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples.

Changchang Liu;Supriyo Chakraborty;Prateek Mittal

208
Citations
RAPTOR: routing attacks on privacy in tor

Yixin Sun;Anne Edmundson;Laurent Vanbever;Oscar Li

200
Citations
Towards a Timely Causality Analysis for Enterprise Security.

Yushan Liu;Mu Zhang;Ding Li;Kangkook Jee

184
Citations
DECENT: A decentralized architecture for enforcing privacy in online social networks

S. Jahid;S. Nilizadeh;P. Mittal;N. Borisov

163
Citations
Dimensionality Reduction as a Defense against Evasion Attacks on Machine Learning Classifiers.

Arjun Nitin Bhagoji;Daniel Cullina;Prateek Mittal

163
Citations
Cachet: a decentralized architecture for privacy preserving social networking with caching

Shirin Nilizadeh;Sonia Jahid;Prateek Mittal;Nikita Borisov

162
Citations
RobustBench: a standardized adversarial robustness benchmark.

Francesco Croce;Maksym Andriushchenko;Vikash Sehwag;Edoardo Debenedetti

82
Citations
HYDRA: Pruning adversarially robust neural networks

Vikash Sehwag;Shiqi Wang;Prateek Mittal;Suman Jana

53
Citations

Frequent Co-Authors

Mung Chiang Purdue University West Lafayette

Nikita Borisov University of Illinois at Urbana-Champaign

Sanjeev R. Kulkarni Princeton University

Shouling Ji Zhejiang University

Dawn Song University of California, Berkeley

Nick Feamster University of Chicago

H. Vincent Poor Princeton University

Jennifer Rexford Princeton University

Neil Zhenqiang Gong Duke University

Matthew Caesar University of Illinois at Urbana-Champaign

External Links

Personal website of Prateek Mittal Google Scholar page

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