• Field of Research: Community Detection (Graph Algorithms)
  • Supervisor: Dr. Fahimeh Dabaghi-Zarandi
  • Department: “Computer Engineering” department of “Vali-e-Asr University of Rafsanjan”.
  • Date: Aug 2021 – March 2024
  • My key role consisted of:
    • Conducted a comprehensive review of prior work in graph-based community detection.
    • Designed and implemented CRLG, a randomized community detection framework leveraging both local and global network information.
    • Developed weighted probabilistic seeding and similarity-driven community assignment with heuristic community merging.
    • Implemented and evaluated the framework in MATLAB and Python, including validation, testing, and performance tuning.
    • Evaluated on real-world networks and GN/LFR benchmarks, achieving up to 10% improvement over LCDR, MOACO, Node2Vec-SC, NE-N2V, CDASS, and TS using NMI, modularity, and density metrics.
  • We have published one paper in the JNCA journal[1].

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