LabCompass

Vijay Raghunathan

Engineering · Purdue University West Lafayette

Established · publishing since 2000Rising activity

Publications

165

Citations

7,689

Est. group size

~3

Recurring co-author estimate

Active years

27

Publishing since 2000

Research summary
AI-generated

Vijay Raghunathan works on making computing hardware and systems more energy-efficient, particularly for embedded devices, edge computing, and Internet of Things (IoT) applications. Recent work focuses on designing specialized chips called Neural Processing Units (NPUs) that efficiently run AI models like graph neural networks and other emerging network architectures on small, resource-limited devices. His research also explores approximate computing, a technique that trades a small amount of accuracy for large energy savings across sensing, computing, memory, and communication systems.

Energy-efficient computing and edge AI hardwareNeural network acceleration on specialized processors (NPUs)Approximate computing for energy-accuracy tradeoffsEmbedded systems and wireless sensor networksHardware security for embedded/IoT devices

Publication output dipped in the early 2020s (including a gap in 2022) but has picked up again since 2024, with 2025 showing notably higher activity.

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

Publication cadence
Publications per year over the last 10 years — averaging 3.8/year recently
2017: 11 publications11172018: 6 publications182019: 3 publications192020: 6 publications202021: 3 publications21222023: 3 publications232024: 4 publications242025: 8 publications252026: 4 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×8
  • ACM Transactions on Embedded Computing Systems×7
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems×5
  • IEEE Transactions on Multi-Scale Computing Systems×2
  • IEEE Embedded Systems Letters×2
Similar researchers
By research-topic overlap

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.

Claim or correct this profile