World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7063
World Ranking
9701
National Ranking
4103

Overview

Kush R. Varshney is affiliated with IBM in the United States. Their research primarily focuses on the field of Computer Science, with a significant concentration on subfields such as Artificial Intelligence, Safety Research, Statistics and Probability, Health Informatics, and Molecular Biology.

Their work covers a range of topics including Explainable Artificial Intelligence (XAI), Ethics and Social Impacts of AI, Adversarial Robustness in Machine Learning, Topic Modeling, Artificial Intelligence in Healthcare and Education, Privacy-Preserving Technologies in Data, and Natural Language Processing Techniques.

Varshney has published extensively, with notable papers including:

  • "Socially Responsible AI Algorithms: Issues, Purposes, and Challenges," 2021, Journal of Artificial Intelligence Research
  • "Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making," 2022, Proceedings of the ACM on Human-Computer Interaction
  • "Data Augmentation for Discrimination Prevention and Bias Disambiguation," 2020, Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  • "A synergistic future for AI and ecology," 2023, Proceedings of the National Academy of Sciences
  • "Socially Responsible AI Algorithms: Issues, Purposes, and Challenges," 2021, arXiv (Cornell University)

Frequent co-authors collaborating with Varshney include Prasanna Sattigeri, Amit Dhurandhar, Karthikeyan Shanmugam, Pierre Dognin, and Inkit Padhi.

Their research contributions have been featured most frequently in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Proceedings of the AAAI/ACM Conference on AI Ethics and Society, Nature Machine Intelligence, and the Proceedings of the International AAAI Conference on Web and Social Media.

Best Publications

  • AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias

    R. K. E. Bellamy;K. Dey;M. Hind;S. C. Hoffman

  • Optimized Pre-Processing for Discrimination Prevention

    Flávio du Pin Calmon;Dennis Wei;Bhanukiran Vinzamuri;Karthikeyan Natesan Ramamurthy

  • AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

    Rachel K. E. Bellamy;Kuntal Dey;Michael Hind;Samuel C. Hoffman

  • FactSheets: Increasing trust in AI services through supplier's declarations of conformity

    M. Arnold;R. K. E. Bellamy;M. Hind;S. Houde

  • Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing

    Mujdat Cetin;Ivana Stojanovic;Ozben Onhon;Kush Varshney

  • One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

    Vijay Arya;Rachel K. E. Bellamy;Pin-Yu Chen;Amit Dhurandhar

  • Socially Responsible AI Algorithms: Issues, Purposes, and Challenges

    Lu Cheng;Kush R. Varshney;Huan Liu

  • Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar

    K.R. Varshney;M. Cetin;J.W. Fisher;A.S. Willsky

  • On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products

    Kush R. Varshney;Homa Alemzadeh

  • The Effect of Extremist Violence on Hateful Speech Online

    Alexandra Olteanu;Carlos Castillo;Jeremy Boy;Kush R. Varshney

  • Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making.

    Charvi Rastogi;Yunfeng Zhang;Dennis Wei;Kush R. Varshney

  • Fairness GAN: Generating datasets with fairness properties using a generative adversarial network

    Prasanna Sattigeri;Samuel C. Hoffman;Vijil Chenthamarakshan;Kush R. Varshney

  • Engineering safety in machine learning

    Kush R. Varshney

  • The Effect of Extremist Violence on Hateful Speech Online

    Alexandra Olteanu;Carlos Castillo;Jeremy Boy;Kush R. Varshney

  • Bias Mitigation Post-processing for Individual and Group Fairness

    Pranay K. Lohia;Karthikeyan Natesan Ramamurthy;Manish Bhide;Diptikalyan Saha

  • TED: Teaching AI to Explain its Decisions

    Michael Hind;Dennis Wei;Murray Campbell;Noel C. F. Codella

  • Exact Rule Learning via Boolean Compressed Sensing

    Dmitry Malioutov;Kush Varshney

  • Invariant Risk Minimization Games

    Kartik Ahuja;Karthikeyan Shanmugam;Kush Varshney;Amit Dhurandhar

  • Collaborative Kalman Filtering for Dynamic Matrix Factorization

    John Z. Sun;Dhruv Parthasarathy;Kush R. Varshney

  • How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

    Yaoli Mao;Dakuo Wang;Michael Muller;Kush R. Varshney

  • Data Augmentation for Discrimination Prevention and Bias Disambiguation

    Shubham Sharma;Yunfeng Zhang;Jesús M. Ríos Aliaga;Djallel Bouneffouf

  • Fair Transfer Learning with Missing Protected Attributes

    Amanda Coston;Karthikeyan Natesan Ramamurthy;Dennis Wei;Kush R. Varshney

  • Fairness of Classifiers Across Skin Tones in Dermatology

    Newton M. Kinyanjui;Timothy Odonga;Celia Cintas;Noel C. F. Codella

  • Targeting Villages for Rural Development Using Satellite Image Analysis

    Kush R. Varshney;George H. Chen;Brian Abelson;Kendall Nowocin

  • Increasing Trust in AI Services through Supplier's Declarations of Conformity

    Michael Hind;Sameep Mehta;Aleksandra Mojsilovic;Ravi Nair

  • Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

    Sanghamitra Dutta;Dennis Wei;Hazar Yueksel;Pin-Yu Chen

  • Sparsity-Driven Synthetic Aperture Radar Imaging

    Ivana Stojanovic;Kush R. Varshney;Sadegh Samadi;W. Clem Karl

Frequent Co-Authors

Aleksandra Mojsilovic
Aleksandra Mojsilovic IBM (United States)
Michael Hind
Michael Hind IBM (United States)
Lav R. Varshney
Lav R. Varshney University of Illinois at Urbana-Champaign
Jun Wang
Jun Wang University College London
Rachel K. E. Bellamy
Rachel K. E. Bellamy IBM (United States)
Mujdat Cetin
Mujdat Cetin University of Rochester
Jinfeng Yi
Jinfeng Yi IBM (United States)
Pin-Yu Chen
Pin-Yu Chen IBM (United States)
Dongping Fang
Dongping Fang Tsinghua University

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