Research

Research interests and focus areas

My doctoral research focuses on Block Probabilistic Distance Clustering (BPDQ) and its diagnostic measures — work that has resulted in peer-reviewed publications, R packages on CRAN, and invited conference presentations.

Research Interests

Cluster Analysis
Block Clustering
Probabilistic Distance Methods
Cluster Diagnostics
Statistical Computing
Survey Analytics
Applied Statistics

PhD Research

Contributions to Block Clustering and its Diagnostic Measures

Institution Pondicherry University
Supervisor Dr. Kiruthika
Period February 2021 – March 2026
PhD Awarded March 2026

Key Contributions

  1. Density-Based Silhouette Diagnostics — Proposed novel silhouette diagnostics for evaluating soft clustering algorithms, extending the classical silhouette framework to accommodate fuzzy and probabilistic cluster memberships.

  2. Block Probabilistic Distance Clustering — Developed a unified framework for block (co-)clustering using probabilistic distance methods, with theoretical foundations and extensive empirical validation.

  3. R Packages — Built and published open-source software:

    • Silhouette — CRAN package for proximity measure based diagnostics
    • blockclusterPDQ — R package for block probabilistic distance clustering

Research Output

Type Count
Peer-reviewed journal articles 1
Preprints 2
R packages (CRAN / GitHub) 2
Conference papers presented 3
Poster presentations 1

📖 See all publications →

View complete list of publications, preprints, and conference papers.

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