2026 Kamalika Chaudhuri: 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	43	7876	7649	3404	3275	150	9594

Overview

Kamalika Chaudhuri is affiliated with the University of California, San Diego in the United States. Their research primarily falls within the field of Computer Science, with a particular focus on Artificial Intelligence, Computer Vision and Pattern Recognition, and Statistics and Probability. Other subfields include Sociology and Political Science as well as Computer Networks and Communications.

The scientist's work covers a range of topics related to machine learning and data privacy. Key themes in their research include Privacy-Preserving Technologies in Data, Adversarial Robustness in Machine Learning, Cryptography and Data Security, Machine Learning and Algorithms, Domain Adaptation and Few-Shot Learning, Generative Adversarial Networks and Image Synthesis, and Machine Learning and Data Classification.

Selected recent papers authored or co-authored by Kamalika Chaudhuri are as follows:

"A Closer Look at Accuracy vs. Robustness", 2020, arXiv (Cornell University)
"Approximate Data Deletion from Machine Learning Models", 2020, arXiv (Cornell University)
"An Introduction to Vision-Language Modeling", 2024, arXiv (Cornell University)
"Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model", 2022, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
"A Non-Parametric Test to Detect Data-Copying in Generative Models", 2020, arXiv (Cornell University)

Frequent co-authors with whom Kamalika Chaudhuri has collaborated include:

Chuan Guo
Casey Meehan
Jacob Imola
Robi Bhattacharjee
Ruihan Wu

The main venues where their work has been published include:

arXiv (Cornell University)
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
Journal of Artificial Intelligence Research
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
IEEE Journal on Selected Areas in Information Theory

Best Publications

Differentially Private Empirical Risk Minimization

Kamalika Chaudhuri;Claire Monteleoni;Anand D. Sarwate

1402
Citations
Multi-view clustering via canonical correlation analysis

Kamalika Chaudhuri;Sham M. Kakade;Karen Livescu;Karthik Sridharan

951
Citations
Privacy-preserving logistic regression

Kamalika Chaudhuri;Claire Monteleoni

753
Citations
Stochastic gradient descent with differentially private updates

Shuang Song;Kamalika Chaudhuri;Anand D. Sarwate

605
Citations
Privacy, accuracy, and consistency too: a holistic solution to contingency table release

Boaz Barak;Kamalika Chaudhuri;Cynthia Dwork;Satyen Kale

566
Citations
Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model

Kamalika Chaudhuri;Fan Chung;Alexander Tsiatas

263
Citations
Signal Processing and Machine Learning with Differential Privacy: Algorithms and Challenges for Continuous Data

A. D. Sarwate;K. Chaudhuri

257
Citations
Paths, trees, and minimum latency tours

K. Chaudhuri;B. Godfrey;S. Rao;K. Talwar

224
Citations
Selfish caching in distributed systems: a game-theoretic analysis

Byung-Gon Chun;Kamalika Chaudhuri;Hoeteck Wee;Marco Barreno

220
Citations
Location determination of a mobile device using IEEE 802.11b access point signals

Unknown

217
Citations
Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics

Xi Wu;Fengan Li;Arun Kumar;Kamalika Chaudhuri

201
Citations
Near-optimal Differentially Private Principal Components

Kamalika Chaudhuri;Anand Sarwate;Kaushik Sinha

164
Citations
A near-optimal algorithm for differentially-private principal components

Kamalika Chaudhuri;Anand D. Sarwate;Kaushik Sinha

162
Citations
Pufferfish Privacy Mechanisms for Correlated Data

Shuang Song;Yizhen Wang;Kamalika Chaudhuri

148
Citations
Rates of convergence for the cluster tree

Kamalika Chaudhuri;Sanjoy Dasgupta

143
Citations
iDASH: integrating data for analysis, anonymization, and sharing

Lucila Ohno-Machado;Vineet Bafna;Aziz A Boxwala;Brian E Chapman

138
Citations
A Parameter-free Hedging Algorithm

Kamalika Chaudhuri;Yoav Freund;Daniel J. Hsu

134
Citations
Rates of Convergence for Nearest Neighbor Classification

Kamalika Chaudhuri;Sanjoy Dasgupta

131
Citations
When random sampling preserves privacy

Kamalika Chaudhuri;Nina Mishra

121
Citations
Sample Complexity Bounds for Dierentially Private Learning

Kamalika Chaudhuri;Daniel Hsu

119
Citations
A Closer Look at Accuracy vs. Robustness

Yao-Yuan Yang;Cyrus Rashtchian;Hongyang Zhang;Russ R. Salakhutdinov

106
Citations
Exploring Connections Between Active Learning and Model Extraction

Varun Chandrasekaran;Kamalika Chaudhuri;Irene Giacomelli;Somesh Jha

67
Citations
Approximate Data Deletion from Machine Learning Models: Algorithms and Evaluations.

Zachary Izzo;Mary Anne Smart;Kamalika Chaudhuri;James Y. Zou

19
Citations
Signal Processing and Machine Learning with Differential Privacy

Anand D. Sarwate;Kamalika Chaudhuri

9
Citations
Near-Optimal Algorithms for Differentially-Private Principal Components

Kamalika Chaudhuri;Anand D. Sarwate;Kaushik Sinha

5
Citations

Frequent Co-Authors

Daniel Hsu Columbia University

Tara Javidi University of California, San Diego

Satish Rao University of California, Berkeley

Sanjoy Dasgupta University of California, San Diego

Max Welling University of Amsterdam

Somesh Jha University of Wisconsin–Madison

Kunal Talwar Apple (United States)

Ruslan Salakhutdinov Carnegie Mellon University

Robert E. Tarjan Princeton University

Shuang Song Harbin Institute of Technology

External Links

Personal website of Kamalika Chaudhuri Google Scholar page

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