Arun Rajkumar
Arun Rajkumar is a machine-learning researcher at IIT Madras whose work spans private classification, pairwise ranking and sequential decision-making. He studied in Neyveli, trained in engineering at PSG College of Engineering and in computer science and machine learning at IISc, then worked at Cisco and Xerox Research before joining IIT Madras in 2019. His research includes privacy-preserving classification, feature-based rankings, rankings under adversarial votes and bandit learning; he received IIT Madras's Young Faculty Recognition Award in 2022. As of October 2026, he is an assistant professor at IIT Madras's Wadhwani School of Data Science and AI.
- Now at
- IIT Madras
- Badges
Timeline
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2012
Private multiparty classification
In 2012, he coauthors a differentially private stochastic-gradient algorithm for classification across data held by several parties.
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2015
Condorcet winners in cyclic rankings
In 2015, with Suprovat Ghoshal, Lek-Heng Lim and Shivani Agarwal, he develops ranking algorithms that recover Condorcet winners and tournament solution sets from stochastic pairwise preferences that can contain cycles.
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2017
Inductive Pairwise Ranking
In 2017, with U. N. Niranjan, he introduces Inductive Pairwise Ranking, which uses item features and matrix completion to learn rankings from sparsely sampled comparisons.
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March 2019–May 2025
From Neyveli to IIT Madras
He studies in Neyveli near Chennai, moves to Coimbatore for engineering at PSG College of Engineering, then earns an MS in computer science and a PhD in machine learning at IISc. After his undergraduate degree, he works at Cisco; after his PhD, he works as a research scientist at Xerox Research. He joins IIT Madras as an assistant professor in March 2019, and teaches Pattern Recognition and Machine Learning in January–May 2024 and Introduction to Programming in January–May 2025.
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2021–2022
Deployable AI and a faculty award
In 2021, he serves as a project investigator at IIT Madras's Centre for Deployable AI, where he works on fairness, bias, explainability, ethics and privacy. His lab studies theoretical machine learning and sequential decision-making. In June 2021, he chairs the First Conference on Deployable AI, and he receives IIT Madras's Young Faculty Recognition Award in 2022.
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2022
Byzantine Spectral Ranking
With Arnhav Datar and John Augustine, he coauthors Byzantine Spectral Ranking, an algorithm that produces a reliable ranking when good voters outnumber Byzantine voters.
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March 2026
Bandit learning with control variates
In March 2026, he coauthors UCB-LCV, a bandit algorithm that combines estimators from rewards and control variates.
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As of October 2026
Assistant professor at IIT Madras
As of October 2026, he is an assistant professor at IIT Madras's Wadhwani School of Data Science and AI. His research interests include machine learning, rank aggregation and statistical learning.
Career
- Since 2021IIT MadrasProject Investigator
- Until 2019Xerox
Education
- PSG College of EngineeringUndergraduate degree
- Indian Institute of ScienceMS
Sources and credits
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- A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification
- Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top
- Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier
- Meet Dr. Arun Rajkumar | Wadhwani School of Data Science and Artificial Intelligence
- Arun Rajkumar
- Department of Computer Science and Engineering | Indian Institute Of Technology Madras, Chennai
- Young Faculty Recognition Award
- Byzantine Spectral Ranking
- Stochastic Multi-Armed Bandits with Limited Control Variates
- Arun Rajkumar | Wadhwani School of Data Science and Artificial Intelligence