Research & Teaching

Research

My doctoral research focuses on machine learning applied to financial technology (Fintech), with emphasis on explainability, optimization, and risk assessment.

Thesis: “Optimización y Explicabilidad de Machine Learning en Fintech” Supervised by Javier Arroyo Gallardo, Universidad Complutense de Madrid. Expected defense: summer 2026.

Research Areas

Finance & Credit Risk Profit-sensitive machine learning for credit scoring in P2P lending, stock selection with ML classifiers, and conformal prediction for uncertainty quantification in financial models.

Machine Learning & Explainability Hyperparameter optimization with genetic algorithms, SHAP-based model explanation, and conformal prediction frameworks (MAPIE, Crepes) for regulated industries.

Music Information Retrieval Automatic genre classification in electronic dance music, audio feature extraction, and taxonomic analysis of subgenre relationships.

Teaching

Adjunct Professor (Profesor Colaborador) Universitat Oberta de Catalunya (UOC) · 2021 – present

  • Course: Fundamentos de la Ciencia de Datos (6 ECTS), Master in Data Science program
  • Responsibilities: course material development, student assessment, forum moderation, and virtual tutoring

Thesis Co-supervision Universidad Complutense de Madrid · 2023

  • Bachelor’s Thesis (TFG): “Performance assessment of credit risk models with boosting algorithms and transfer learning from Large Language Models”
  • Student: Mario Sanz Guerrero · Co-supervised with Javier Arroyo Gallardo
  • Handle: hdl.handle.net/20.500.14352/101304

Education

Ph.D. in Data Science and Computer Engineering (in progress) Universidad Complutense de Madrid · 2020 – present Thesis: “Optimización y Explicabilidad de Machine Learning en Fintech”

MSc in Data Science Universitat Oberta de Catalunya (UOC) · 2018 – 2021 72 ECTS · GPA: 8.05/10 Thesis: Portfolio optimization with ML using walk-forward methodology

MA in Business Consulting – Data Science specialization ICADE Business School (Comillas) · 2017 – 2019

BSc in Computer Engineering Universidad Complutense de Madrid · 2012 – 2017 246 ECTS · GPA: 7.71/10 Thesis: Automatic classification of electronic music subgenres (grade: 10/10)