LabCompass

Rajiv Khanna

Engineering · Purdue University West Lafayette

OpenAlex ORCID
Established · publishing since 1990
Sparse and Compressive Sensing TechniquesStochastic Gradient Optimization TechniquesMachine Learning and AlgorithmsDomain Adaptation and Few-Shot LearningStatistical Methods and Inference

Publications

56

Citations

1,192

Est. group size

—

Recurring co-author estimate

Active years

36

Publishing since 1990

Research summary
AI-generated

Rajiv Khanna works on the mathematical foundations of machine learning, focusing on how training algorithms and data selection methods behave and why they generalize (or fail to). His work covers topics like data summarization (coresets), understanding optimizer stability (e.g., SGD, SAM), robustness of deep networks, and efficient methods for large-scale computation such as distributed learning and matrix approximation. This research is largely theoretical/methodological, aiming to explain and improve the reliability and efficiency of machine learning systems.

Theoretical foundations of machine learning optimizationData selection, summarization, and coresetsRobustness and generalization of deep neural networksScalable and distributed learning algorithmsSparse/low-rank approximation methods (e.g., matrix sketching)

Publication output was relatively high around 2017-2020, dropped sharply in 2021-2023, and has shown a modest uptick in 2024-2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 1.4/year recently
2017: 10 publications10172018: 7 publications182019: 4 publications192020: 10 publications10202021: 3 publications21222023: 1 publication232024: 2 publications242025: 4 publications2526
Recent publications
Publishes in
  • arXiv (Cornell University)×30
  • International Conference on Artificial Intelligence and Statistics×4
  • Society for Industrial and Applied Mathematics eBooks×2
  • Neural Information Processing Systems×1
  • The Annals of Statistics×1
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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