LabCompass

David F. Gleich

Physics and Astronomy · Purdue University West Lafayette

Mid career · publishing since 2003

Publications

220

Citations

5,776

Est. group size

~2

Recurring co-author estimate

Active years

24

Publishing since 2003

Research summary
AI-generated

David F. Gleich works on the mathematics and computing methods behind analyzing large networks and graphs, including tools like graph matrices, clustering, and higher-order structures called hypergraphs (where relationships can involve more than two items at once). His work also extends into designing specialized computer hardware and optimization algorithms to process these large-scale graph datasets more efficiently.

Graph and network analysis algorithmsHypergraphs and higher-order network structuresSpectral and matrix methods for graphsParallel/supercomputer architectures for graph processingOptimization algorithms for machine learning

Publication output was steady at around 14-16 papers per year from 2017-2020, then declined to a lower and more variable pace of roughly 4-10 papers per year from 2021 onward.

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

Publication cadence
Publications per year over the last 10 years — averaging 7.2/year recently
2017: 14 publications172018: 14 publications182019: 14 publications192020: 16 publications16202021: 7 publications212022: 7 publications222023: 9 publications232024: 4 publications242025: 10 publications252026: 6 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×42
  • Zenodo (CERN European Organization for Nuclear Research)×4
  • SIAM Journal on Scientific Computing×3
  • Society for Industrial and Applied Mathematics eBooks×3
  • Studies in computational intelligence×3
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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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