LabCompass

Atul Sharma

Computer Science · Purdue University West Lafayette

Established · publishing since 1970

Publications

11

Citations

65

Est. group size

~1

Recurring co-author estimate

Active years

56

Publishing since 1970

Research summary
AI-generated

Atul Sharma's recent work focuses on the security and privacy of federated learning, a technique where multiple devices or organizations train a shared machine learning model without directly sharing their raw data. His publications examine ways attackers can reconstruct private data or manipulate models (data reconstruction and poisoning attacks) as well as defenses to protect against such attacks. Earlier work also touched on software engineering topics and computer-based learning tools.

Federated learning securityPrivacy attacks on machine learning modelsDefenses against model poisoningPeer-to-peer and collaborative learning systemsSoftware engineering and developer behavior analysis

Publication output has been low and irregular over the last decade, averaging fewer than one paper per year in the most recent five years, with no clear growth or decline pattern.

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

Publication cadence
Publications per year over the last 10 years — averaging 0.8/year recently
2017: 1 publication17182019: 2 publications2192020: 2 publications2202021: 1 publication21222023: 2 publications2232024: 1 publication242025: 1 publication2526
Publishes in
  • arXiv (Cornell University)×3
  • International Journal of Innovative Research in Computer Science & Technology×1
  • Solid State Technology×1
  • SSRN Electronic Journal×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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