Alejandro Polo Molina

Alejandro Polo Molina is a Predoctoral Researcher at the Intelligent Systems Area of the Instituto de Investigación Tecnológica (IIT), part of Comillas Pontifical University's Higher Technical School of Engineering. He joined IIT in September 2022 after completing advanced degrees in data science and holding industry positions at Repsol and Accenture.

His academic credentials include a Bachelor's degree in Mathematics from the University of Granada (2020), a Master's in Big Data and Advanced Analytics from Comillas Pontifical University (2021), and a Master's in Big Data & Visual Analytics from UNIR (2021).

• Bachelor of Mathematics, University of Granada (2020)
• Master in Big Data and Advanced Analytics, Comillas Pontifical University (2021)
• Master in Big Data & Visual Analytics, International University of La Rioja (2021)

Polo Molina's research spans Deep Learning, Machine Learning, Time Series Prediction, and Graph Machine Learning, with applications in healthcare analytics, automotive safety, and theoretical neural network guarantees. His work emphasizes interpretable AI models for clinical decision support and physical system modeling, particularly through Kolmogorov-Arnold Networks for certified monotonicity in ethical AI applications. He develops practical solutions for time-series forecasting in energy markets and patient mobility analysis using wearable sensors.

His publication record (2023-2025) reveals strong interdisciplinary trends, bridging machine learning with biomedical engineering and automotive safety. Key themes include clinical condition prediction for chronic patients using wearable data, interpretable thoracic injury modeling in car crashes, and mathematical certification frameworks for neural network behavior. His work consistently connects theoretical guarantees with real-world applications in high-stakes domains.

Polo Molina has secured research funding through multiple industry and government projects, including Endesa Medios y Sistemas SL for residual demand curve forecasting, Innomerics S.L. for green hydrogen plant methodologies, and the Spanish Ministry of Science for chronic patient movement analysis. These projects demonstrate his ability to translate academic research into industrial solutions while maintaining rigorous scientific standards.

As an emerging researcher at IIT, he actively contributes to the Intelligent Systems group through conference presentations at venues like IRCOBI Europe and SEIO, invited seminars on neural network theory, and collaborative projects spanning healthcare, energy, and automotive sectors. His trajectory shows rapid progression from industry data science roles to cutting-edge academic research with significant practical impact.