Enrique Mateos-Melero
PhD Student
About Me
I am a Ph.D. student at Universidad Carlos III de Madrid, Spain. I work at the Computer Science and Engineering Department, in the Planning & Learning Group (PLG). My main research areas are Reinforcement Learning (RL) and Machine Learning (ML) applications. My work focuses on optimizing decision-making systems, particularly in environments that balance efficiency and sustainability.
Short bio
I got my bachelor's on Computer Science and Engineering at Universidad Carlos III de Madrid and my master's on Applied Artificial Intelligence at the same university. I got the Best Academic Record Award for the Computer Science and Engineering Promotion of 2022/23. I have collaborated with Repsol S.A. in several projects involving Reinforcement Learning in industrial environments and on a multi-agent RL environment that simulates a city with fuel and electric vehicles, exploring strategies for transitioning refueling stations from fuel pumps to electric chargers.
Publications
2025
Enrique Mateos-Melero, Miguel Iglesias Alcázar, Raquel Fuentetaja and Fernando Fernández.
Dataset Reduction for Offline Reinforcement Learning using Genetic Algorithms with Image-Based Heuristics.
In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 416–424. 2025.
paper citationEnrique Mateos-Melero, Javier Moralejo-Piñas, Francisco Martínez-Gil, María Soriano and Fernando Fernández.
Evolutionary Optimization of the Gas/Charging Stations Topology for the Electric Vehicle Market.
In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 867–870. 2025.
paper citationEnrique Mateos-Melero.
Efficient Offline Reinforcement Learning Through Dataset Characterization and Reduction.
In Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, pp. 2950–2952. 2025.
paper citationEnrique Mateos-Melero, Javier Moralejo-Piñas, Angela Durán-Pinto, Francisco Martínez-Gil, María Soriano and Fernando Fernández.
Where is the Nearest EV Charging Station? Evolutionary Optimization of the Gas/charging Stations Topology.
In Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, pp. 2666–2668. 2025.
paper citation
2024
Enrique Mateos-Melero, Miguel Iglesias Alcázar, Raquel Fuentetaja, Peter Stone and Fernando Fernández.
Image-based Dataset Representations for Predicting Learning Performance in Offline RL.
In . 2024.
paper citation