LabCompass

David J. Love

Engineering · Purdue University West Lafayette

Established · publishing since 1993Rising activity

Publications

493

Citations

17,464

Est. group size

~18

Recurring co-author estimate

Active years

34

Publishing since 1993

Research summary
AI-generated

David J. Love works on wireless communication systems, with a focus on large antenna arrays (massive MIMO), millimeter-wave and next-generation (6G) networks, and how these systems can be made more efficient, secure, and intelligent using machine learning. His recent work spans topics like integrated sensing and communication, federated learning over wireless networks, reconfigurable intelligent surfaces, and satellite and vehicle-to-grid communication systems. Students in this group would likely engage with mathematically grounded wireless system design combined with applied machine learning techniques.

Massive MIMO and antenna array systemsMachine learning for wireless networks (including federated learning)Integrated sensing and communication (ISAC)Next-generation (6G) wireless and network infrastructureResource allocation and system optimization in communication networks

Publication output has grown over the past decade, rising from around 20 papers per year in 2017-2019 to a peak near 47 in 2023, with recent years remaining high (around 28-31 per year).

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

Publication cadence
Publications per year over the last 10 years — averaging 29.6/year recently
2017: 23 publications172018: 19 publications182019: 18 publications192020: 22 publications202021: 23 publications212022: 30 publications222023: 47 publications47232024: 31 publications242025: 28 publications252026: 12 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×71
  • IEEE Transactions on Wireless Communications×19
  • IEEE Journal on Selected Areas in Communications×9
  • IEEE Transactions on Communications×9
  • IEEE Communications Letters×8
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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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