Raúl Martín Santamaría

PhD in Artificial Intelligence

Bio

Raúl Martín Santamaría is a Professor/Assistant Doctor (Profesor Ayudante Doctor) at Universidad Rey Juan Carlos, specifically at the School of Computer Engineering in the Department of Computer Science and Artificial Intelligence. He completed his PhD in Artificial Intelligence at Universidad Rey Juan Carlos in 2023 under the direction of Abraham Duarte Muñoz and José Manuel Colmenar Verdugo.

He is a member of the GRAFO (Group for Research in Algorithms For Optimization) research group at Universidad Rey Juan Carlos, specializing in the intersection of artificial intelligence, metaheuristics, and cybersecurity. His research focuses on applying advanced optimization techniques to solve complex problems in security and privacy domains, with particular emphasis on the automatic generation of metaheuristic algorithms.

Research Focus

Automatic Generation of Metaheuristics: His doctoral thesis, titled “On the automatic generation of metaheuristic algorithms for combinatorial optimization problems,” presents a new methodology for the automated generation of reproducible metaheuristic configurations. This work addresses critical issues of reproducibility and reusability in metaheuristic algorithms.

Mork Framework: He developed Mork (Metaheuristic Optimization framewoRK), a reference implementation for developing approaches to NP-Hard problems using the JVM. This framework provides a systematic approach to metaheuristic algorithm development and testing.

Combinatorial Optimization: His research encompasses heuristics and metaheuristics, trajectory algorithms, genetic algorithms, and multi-objective problems, with most of his publications dealing with the development of heuristic and metaheuristic procedures to solve complex optimization problems.

Cybersecurity Applications: He bridges theoretical optimization research with practical cybersecurity applications, developing AI-driven solutions for security challenges.

Education

• PhD in Artificial Intelligence - Universidad Rey Juan Carlos (2019-2023)
  • Thesis: “On the automatic generation of metaheuristic algorithms for combinatorial optimization problems”
  • Directors: Abraham Duarte Muñoz and José Manuel Colmenar Verdugo
• MEng in Cybersecurity and Privacy - Universitat Oberta de Catalunya (2018-2019)
• Computer Science & Software Engineering - Universidad Rey Juan Carlos (2014-2018)

Key Publications & Contributions

• “On the automatic generation of metaheuristic algorithms for combinatorial optimization problems” - Doctoral thesis (2023)
• Mork Framework - Metaheuristic Optimization framewoRK for JVM-based optimization
• Reproducibility Research - Work on reproducibility of experiments in stochastic methods such as evolutionary algorithms
• Thermal Prediction Models - Building-integrated photovoltaics systems using guided artificial intelligence algorithms

Cybersecurity Achievements

Competition Excellence:

• CTF Winner (2022) - First place in the Capture The Flag competition at the VII National Cybersecurity Research Conference, competing against 277 participants from 93 teams worldwide (with Isaac Lozano Osorio and Sergio Pérez Peló)
• National Cyber League Champion - Winner of the II National Cyber League organized by the Civil Guard (as part of ‘Heappies’ team)
• Bug Bounty Winner - First prize in the cybersecurity contest organized by Universidad Rey Juan Carlos

Spanish National Team: Selected for the ‘Spanish team’ of Cybersecurity, representing Spain in international competitions.

Research Applications

• Automated Algorithm Generation - Systematic approaches to metaheuristic algorithm development
• Optimization Framework Development - JVM-based tools for NP-Hard problem solving
• Cybersecurity Solutions - AI-driven approaches to security challenges
• Reproducible Research - Methods for ensuring reproducibility in stochastic optimization algorithms

Academic Recognition

• Teaching Excellence - Active involvement in cybersecurity education at Universidad Rey Juan Carlos
• Research Leadership - Key member of the GRAFO research group
• International Recognition - National team selection for cybersecurity competitions

Professional Development

• Framework Development - Creator of the Mork framework for metaheuristic optimization
• Industry Applications - Practical implementations of optimization algorithms in real-world scenarios
• Competitive Programming - Demonstrated excellence in cybersecurity competitions at national and international levels

Current Research Areas

• Metaheuristic Automation - Advancing automatic generation of optimization algorithms
• Cybersecurity AI - Developing artificial intelligence solutions for security challenges
• Framework Enhancement - Continued development of the Mork optimization framework
• Reproducible Research - Ensuring scientific rigor in metaheuristic algorithm development

Interests

Artificial Intelligence | Metaheuristics | Cybersecurity | Combinatorial Optimization | Framework Development | Reproducible Research

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