Posts by Collection

portfolio

db-robust-clust

A Python package with robust, distance-based clustering algorithms (including Fast K-Medoids and Q-Fold Fast K-Medoids) for large volumes of mixed-type data.

robust-mixed-dist

A Python package implementing robust statistical distances for mixed-type multivariate data, developed as part of my PhD research.

publications

On generalized Gower distance for mixed-type data: extensive simulation study and new software tools

Published in SORT - Statistics and Operations Research Transactions, 2025

Robust distances for mixed-type data, namely robust generalized Gower and robust related metric scaling, together with a new Python package implementing them.

Recommended citation: Grané, A., & Scielzo-Ortiz, F. (2025). "Robust distances for mixed-type data: Robust generalized Gower and robust related metric scaling." SORT - Statistics and Operations Research Transactions. https://doi.org/10.57645/20.8080.02.28
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New Distance-Based Robust Clustering Algorithms for Large Mixed-Type Data

Published in Advances in Data Analysis and Classification, 2026

New distance-based robust clustering algorithms designed to scale to large volumes of mixed-type multivariate data.

Recommended citation: Grané, A., & Scielzo-Ortiz, F. (2026). "New distance-based robust clustering algorithms for large mixed-type data." Advances in Data Analysis and Classification. https://doi.org/10.1007/s11634-026-00701-9
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Evaluating the Educational Impact of an LLM Virtual Assistant in Video-Based Learning

Published in Submitted to Journal of Computer Assisted Learning (JCAL), 2026

A controlled trial with secondary and vocational students examining whether an LLM-based pedagogical agent layered on instructional video improves learning gains, self-efficacy and cognitive load.

Recommended citation: Scielzo-Ortiz, F., et al. (2026). "Evaluating the educational impact of an LLM virtual assistant in video-based learning." (Submitted to Journal of Computer Assisted Learning).

Quantifying Global Polarization: Detection and Analysis of Opinion Groups on the Gaza Conflict at International Level Based on Reddit Data

Published in Submitted for publication at Journal of Computational Social Sciences (Springer), 2027

A robust computational framework, combining LLM-based feature extraction with robust mixed-data clustering, to detect and analyze international opinion groups on the Gaza conflict from Reddit data.

Recommended citation: Scielzo-Ortiz, F., Grané, A., & Díaz-Gorfinkiel, M. (2026). "Quantifying global polarization: Detection and analysis of opinion groups on the Gaza conflict at international level based on Reddit data." (Submitted for publication).

talks

XLI National Congress in Statistics, Operations Research and Data Science (SEIO 2025)

Published:

Oral communication presenting “Data Science for Decision-Making in Public Health: A robust Clustering Approach for Large-Scale Weighted and Mixed-Type Socio-Economic Data” (co-authored with Aurea Grané and Irene Albarrán), at the XLI National Congress in Statistics and Operations Research (SEIO 2025), Lleida, Spain.

19th Conference of the International Federation of Classification Societies (IFCS 2026)

Published:

Oral communication presenting “Quantifying global polarization: Detection and analysis of opinion groups on the Gaza conflict at international level based on Reddit data” (co-authored with Aurea Grané and Magdalena Díaz-Gorfinkiel), at the 19th Conference of the International Federation of Classification Societies (IFCS 2026), Università degli Studi di Milano Bicocca, Milan, Italy.

XLII National Congress in Statistics, Operations Research and Data Science (SEIO 2026)

Published:

Oral communication presenting “Quantifying global polarization: Detection and analysis of opinion groups on the Gaza conflict at international level based on Reddit data” (co-authored with Aurea Grané and Magdalena Díaz-Gorfinkiel), at the XLII National Congress in Statistics, Operations Research and Data Science in Santiago de Compostela, Spain (SEIO 2026).

teaching

Machine Learning: Supervised Classification

Workshop session, Saturdays AI & ANBAN Data Science Course, Universidad de Elche, 2024

Taught the session “Machine Learning: clasificación supervisada” (Machine Learning: supervised classification) as part of the Data Science course organized by Saturdays AI and ANBAN, held at Universidad de Elche.

Python Programming for Data Science

Bootcamp module, ANBAN Data Science Bootcamp, 2025

Designed and taught the Python Programming for Data Science module of the ANBAN Data Science Bootcamp, covering Python fundamentals and applied programming skills for data science.