2026 Pradeep Ravikumar: 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	56	3980	3868	1894	1827	209	18221

Research.com Recognitions

2014 - Fellow of Alfred P. Sloan Foundation

Overview

Pradeep Ravikumar is affiliated with Carnegie Mellon University in the United States and has a substantial record of contributions in the field of computer science, particularly focusing on artificial intelligence and related subfields. Their research encompasses a wide range of topics within machine learning and its applications.

Ravikumar's recent published papers include the following:

The Risks of Invariant Risk Minimization, 2020, arXiv (Cornell University)
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius, 2020, arXiv (Cornell University)
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
Faith-Shap: The Faithful Shapley Interaction Index, 2022, arXiv (Cornell University)
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing, 2020, arXiv (Cornell University)

The frequent co-authors of Ravikumar's work include:

Bryon Aragam, with 15 collaborations
Chih-Kuan Yeh, with 10 collaborations
Dan Chen, with 8 collaborations
Elan Rosenfeld, with 8 collaborations
Andrej Risteski, with 8 collaborations

Ravikumar has published extensively in several venues, predominantly in arXiv hosted by Cornell University with 54 papers. Other publication venues include:

Proceedings of the AAAI Conference on Artificial Intelligence
Journal of the Royal Statistical Society Series B (Statistical Methodology)
Applied AI Letters
The Annals of Statistics

The main fields of study for Ravikumar are centered on computer science, with a strong focus on artificial intelligence. The subfields further detail their areas of expertise as:

Artificial Intelligence
Statistics and Probability
Management Science and Operations Research
Computer Vision and Pattern Recognition
Control and Systems Engineering

The primary topics of their research work cover:

Adversarial Robustness in Machine Learning
Domain Adaptation and Few-Shot Learning
Machine Learning and Algorithms
Explainable Artificial Intelligence (XAI)
Machine Learning and Data Classification
Anomaly Detection Techniques and Applications
Bayesian Modeling and Causal Inference

In recognition of their work, Pradeep Ravikumar was awarded the title of Fellow of the Alfred P. Sloan Foundation in 2014.

Best Publications

A comparison of string distance metrics for name-matching tasks

William W. Cohen;Pradeep Ravikumar;Stephen E. Fienberg

1993
Citations
A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers

Sahand N. Negahban;Pradeep Ravikumar;Martin J. Wainwright;Bin Yu

1489
Citations
High-dimensional Ising model selection using ℓ1-regularized logistic regression

Pradeep Ravikumar;Martin J. Wainwright;John D. Lafferty

1187
Citations
High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence

Pradeep Ravikumar;Martin J. Wainwright;Garvesh Raskutti;Bin Yu

993
Citations
Learning with Noisy Labels

Nagarajan Natarajan;Inderjit S Dhillon;Pradeep K Ravikumar;Ambuj Tewari

849
Citations
Sparse Additive Models

Pradeep Ravikumar;John Lafferty;Han Liu;Larry Wasserman

799
Citations
Adaptive name matching in information integration

M. Bilenko;R. Mooney;W. Cohen;P. Ravikumar

754
Citations
High-dimensional Ising model selection using ${ll_1}$-regularized logistic regression

Pradeep Ravikumar;Martin J. Wainwright;John D. Lafferty

691
Citations
A Dirty Model for Multi-task Learning

Ali Jalali;Sujay Sanghavi;Chao Ruan;Pradeep K. Ravikumar

487
Citations
DAGs with NO TEARS: Continuous Optimization for Structure Learning

Xun Zheng;Bryon Aragam;Pradeep K. Ravikumar;Eric P. Xing

476
Citations
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation

Cho-jui Hsieh;Inderjit S. Dhillon;Pradeep K. Ravikumar;Mátyás A. Sustik

413
Citations
Information-theoretic lower bounds on the oracle complexity of convex optimization

Alekh Agarwal;Peter L. Bartlett;Pradeep Ravikumar;Martin J. Wainwright

374
Citations
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers

Sahand Negahban;Bin Yu;Martin J Wainwright;Pradeep K. Ravikumar

360
Citations
Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization

A. Agarwal;P. L. Bartlett;P. Ravikumar;M. J. Wainwright

285
Citations
Collaborative filtering with graph information: consistency and scalable methods

Nikhil Rao;Hsiang-Fu Yu;Pradeep Ravikumar;Inderjit S. Dhillon

269
Citations
High-Dimensional Graphical Model Selection Using ell_1-Regularized Logistic Regression

Martin J Wainwright;John D. Lafferty;Pradeep K. Ravikumar

247
Citations
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables

Cho-Jui Hsieh;Matyas A Sustik;Inderjit S Dhillon;Pradeep K Ravikumar

215
Citations
QUIC: quadratic approximation for sparse inverse covariance estimation

Cho-Jui Hsieh;Mátyás A. Sustik;Inderjit S. Dhillon;Pradeep Ravikumar

204
Citations
On the (In)fidelity and Sensitivity of Explanations

Chih-Kuan Yeh;Cheng-Yu Hsieh;Arun Sai Suggala;David I. Inouye

193
Citations
Graphical models via univariate exponential family distributions

Eunho Yang;Pradeep Ravikumar;Genevera I. Allen;Zhandong Liu

188
Citations
Representer Point Selection for Explaining Deep Neural Networks

Chih-Kuan Yeh;Joon Sik Kim;Ian En-Hsu Yen;Pradeep Ravikumar

129
Citations
Learning Sparse Nonparametric DAGs

Xun Zheng;Chen Dan;Bryon Aragam;Pradeep Ravikumar

54
Citations
On the (In)fidelity and Sensitivity for Explanations.

Chih-Kuan Yeh;Cheng-Yu Hsieh;Arun Sai Suggala;David I. Inouye

32
Citations

Frequent Co-Authors

Inderjit S. Dhillon Google (United States)

Martin J. Wainwright MIT

Cho-Jui Hsieh University of California, Los Angeles

John Lafferty Yale University

Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence

Bin Yu University of California, Berkeley

Ambuj Tewari University of Michigan–Ann Arbor

Alekh Agarwal Google (United States)

William W. Cohen Carnegie Mellon University

Arindam Banerjee University of Illinois at Urbana-Champaign

External Links

Personal website of Pradeep Ravikumar Google Scholar page

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