I’m a PhD candidate in Machine Learning working on Unsupervised Learning, Clustering, Pattern Recognition, and Natural Language Processing.
My research focuses on clustering methods, validation, and confidence estimation, with applications to structured and textual data.
Affiliated with the Archimedes Research Unit, Athena Research Center.
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CAKE: Confidence in Assignments via K-partition Ensembles
Confidence estimation for individual clustering assignments from multiple partitions. Published in Machine Learning with Applications (2026).
Paper · arXiv · Code · PyPI -
Composite Silhouette: A Subsampling-based Aggregation Strategy
Subsampling-based internal validation for selecting the number of clusters. Presented at ECML PKDD 2026 and published in the Springer Research Track proceedings.
Paper · arXiv · Code · PyPI -
K-Sil: Silhouette-Driven Instance-Weighted k-means
Silhouette-driven instance weighting for more robust k-means clustering.
Preprint · Code · PyPI
Python packages for clustering, validation, confidence estimation, and statistical analysis are available on my PyPI profile, including cake-ensemble, compsil, k-silhouette, sil-score, intclustval, extclustval, and confinterval.
For publications, research, software, NLP work, and other projects: