LabCompass

Thejaka Amila Kanewala

Computer Science · Indiana University

OpenAlex
Distributed and Parallel Computing SystemsCloud Computing and Resource ManagementScientific Computing and Data ManagementGraph Theory and AlgorithmsParallel Computing and Optimization Techniques

Publications

30

Citations

122

Est. group size

—

Recurring co-author estimate

Active years

11

Publishing since 2014

Research summary
AI-generated

Thejaka Amila Kanewala studies how to run large graph algorithms efficiently across many computers and processors working together. The work focuses on parallel and distributed computing techniques—such as counting triangles, finding shortest paths, and computing independent sets in graphs—while reducing the coordination bottlenecks that slow such systems down. This research connects graph algorithms with high-performance and cloud computing platforms.

Distributed and parallel computingGraph algorithmsSynchronization-avoiding and self-stabilizing methodsHigh-performance computing for data analyticsShared-memory and distributed-memory systems

Publication activity peaked around 2017 and has generally slowed in recent years, averaging under one paper per year over the last five years.

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

Publication cadence
Publications per year over the last 10 years — averaging 0.8/year recently
2017: 6 publications6172018: 2 publications182019: 1 publication192020: 3 publications202021: 4 publications212022: 2 publications222023: 1 publication232024: 1 publication242526
Recent publications
Publishes in
  • arXiv (Cornell University)×6
  • Lecture notes in computer science×2
  • Frontiers in High Performance Computing×1
  • Frontiers in Big Data×1
  • ACM SIGPLAN Notices×1

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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