Jose Manuel Colmenar

Universidad Rey Juan Carlos
Madrid, Spain

Full Professor and Dean

Bio

José Manuel Colmenar (known as “Chema” Colmenar) is a Full Professor and Dean at the Escuela Técnica Superior de Ingeniería Informática (ETSII) at Universidad Rey Juan Carlos (URJC), Madrid. He is a prominent researcher in the field of computational intelligence and evolutionary computation, with particular expertise in grammatical evolution and metaheuristics.

He serves as a senior member of the Group for Research in Algorithms For Optimization (GRAFO) at URJC, where he leads research initiatives in evolutionary algorithms and their applications to complex optimization problems. His work has been cited over 1,084 times, establishing him as a leading authority in the field of bio-inspired optimization algorithms.

Research Focus

Grammatical Evolution: His primary research expertise lies in grammatical evolution applications, particularly for symbolic regression problems. He has developed WebGE, an open-source tool for symbolic regression using grammatical evolution, making these advanced techniques accessible to the broader research community.

Bio-inspired Algorithms: His research encompasses various bio-inspired optimization techniques, including particle swarm optimization, genetic programming, and evolutionary algorithms for solving complex optimization problems.

Multi-objective Optimization: He specializes in multi-objective grammatical evolution, particularly for modeling complex systems such as glucose levels in blood of diabetic patients, demonstrating the practical applications of his theoretical work.

Energy Systems: His work extends to energy demand estimation using particle swarm grammatical evolution, contributing to sustainable energy management solutions.

Education & Career

Full Professor (Catedrático) - Universidad Rey Juan Carlos
Dean - Escuela Técnica Superior de Ingeniería Informática (ETSII), URJC
Research Specialization - Metaheuristics and Operations Research

Leadership & Projects

HOMERO Project: Principal investigator (with Abraham Duarte) of the HOMERO project - “A new holistic methodology for configuration, comparison, and evaluation of metaheuristics” funded by the Spanish Ministry of Science and Innovation.

EMIGO Project: Principal investigator (with Abraham Duarte) of the EMIGO project - “Efficient Metaheuristics for Graph Optimization” focusing on advanced optimization techniques for graph-based problems.

Academic Leadership: As Dean of ETSII at URJC, he oversees academic programs in computer science, telecommunications, and systems engineering, fostering excellence in computational intelligence education.

Key Publications & Contributions

“WebGE: An Open-Source Tool for Symbolic Regression Using Grammatical Evolution” - Development of accessible tools for the research community
“Particle swarm grammatical evolution for energy demand estimation” - Energy Science & Engineering
“Short and Medium Term Blood Glucose Prediction Using Multi-objective Grammatical Evolution” - Healthcare applications of optimization
“Algoritmos Bioinspirados” - Comprehensive work on bio-inspired algorithms

Research Applications

Healthcare Systems - Glucose prediction models for diabetic patients
Energy Management - Demand estimation and optimization
Symbolic Regression - Advanced mathematical modeling techniques
Graph Optimization - Efficient algorithms for complex network problems
Industrial Applications - Metaheuristic solutions for real-world optimization challenges

Academic Recognition

High Citation Impact - Over 1,084 citations reflecting significant research influence
International Collaboration - Active participation in global research networks
Tool Development - Creation of open-source software for the research community
Project Leadership - Principal investigator on major national research grants

Current Research Areas

Multilayer Analysis - Population diversity in grammatical evolution for symbolic regression
Hybrid Metaheuristics - Combining different optimization approaches for enhanced performance
Practical Applications - Real-world implementation of theoretical advances
Open Science - Development of accessible research tools and methodologies