LabCompass

Ariful Azad

Computer Science · Indiana University

OpenAlex ORCID
Graph Theory and AlgorithmsParallel Computing and Optimization TechniquesAdvanced Graph Neural NetworksComplex Network Analysis TechniquesInterconnection Networks and Systems

Publications

143

Citations

1,856

Est. group size

—

Recurring co-author estimate

Active years

21

Publishing since 2006

Research summary
AI-generated

Ariful Azad works in computer science at the intersection of high-performance computing and machine learning on graphs. A central theme is designing fast, scalable algorithms for sparse matrix operations and running them across many processors (distributed-memory systems), and applying these to graph neural networks, network analysis, and forecasting. Recent work also emphasizes making graph neural network predictions more interpretable and explainable.

Sparse matrix and parallel computingGraph neural networksExplainable/interpretable machine learningNetwork analysis and alignmentSpatiotemporal forecasting

Publication activity has been steady over the last decade, with a peak around 2020–2021 and a consistent output of roughly ten papers per year since.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 10.0/year recently
2017: 9 publications172018: 7 publications182019: 6 publications192020: 19 publications19202021: 18 publications212022: 11 publications222023: 8 publications232024: 15 publications242025: 11 publications252026: 5 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×43
  • SSRN Electronic Journal×3
  • Parallel Computing×2
  • IEEE Transactions on Parallel and Distributed Systems×2
  • Journal of Computer Science and Technology Studies×2

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 11, 2026.

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