Marcos Robles
Universidad Rey Juan Carlos
Madrid, Spain
PhD Student in Artificial Intelligence
Bio
Marcos Robles is a PhD student in Artificial Intelligence at Universidad Rey Juan Carlos, working as a predoctoral researcher in the Group for Research in Algorithms For Optimization (GRAFO). He graduated in Software Engineering from Universidad Rey Juan Carlos in 2022 and completed his Master’s degree in Artificial Intelligence Research at Universidad Internacional Menéndez Pelayo in 2023.
Throughout his career, he has worked in a wide range of software fields ranging from web development to artificial intelligence. His research specializes in optimization techniques to solve Graph Layout Problems, a particular class of combinatorial optimization problems whose goal is to find a linear layout of an input graph in such way that a certain objective cost is optimized.
Research Focus
Graph Layout Problems: His primary research focuses on developing optimization techniques for various graph layout problems, including linear arrangement problems, cutwidth minimization, and cyclic arrangement problems.
Minimum Sitting Arrangement: He has conducted research on the Minimum Sitting Arrangement (MinSA) problem, which aims to minimize the total number of errors produced when the graph (input graph) is embedded into another graph (host graph).
Variable Neighborhood Search: His work includes applications of Basic Variable Neighborhood Search (BVNS) methodologies for solving complex graph optimization problems.
Combinatorial Optimization: He specializes in developing metaheuristic algorithms for hard combinatorial optimization problems in graph theory.
Education
- PhD Student in Artificial Intelligence - Universidad Rey Juan Carlos (2023-present)
- Master’s Degree in Artificial Intelligence Research - Universidad Internacional Menéndez Pelayo (2022-2023)
- Software Engineering Degree - Universidad Rey Juan Carlos (2018-2022)
Key Publications
- “Multi-armed bandit for the cyclic minimum sitting arrangement problem” - Co-authored with Sergio Cavero, Eduardo G. Pardo, and Oscar Cordon (2025)
- “BVNS for the Minimum Sitting Arrangement Problem in a Cycle” - Springer publication on Basic Variable Neighborhood Search applications
- Research on Linear Layout Problems - Collaborative work examining relationships between minimum linear arrangement, cutwidth minimization, and related optimization problems
Research Applications
- Linear Arrangement Problems - Optimization of graph layouts in linear structures
- Cutwidth Minimization - Reducing the maximum number of edges crossing any cut
- Cyclic Arrangements - Optimizing circular graph layouts
- Multi-armed Bandit Approaches - Advanced algorithmic techniques for optimization problems
Professional Experience
Software Development Background: His diverse experience spans web development to artificial intelligence applications, providing practical insights into real-world optimization challenges.
Research Collaboration: Active collaboration within the GRAFO research group, working with senior researchers including Sergio Cavero, Eduardo G. Pardo, and Oscar Cordon.
Current Research Projects
- Graph Layout Optimization - Developing novel metaheuristic approaches for graph layout problems
- Cyclic Arrangement Problems - Advanced algorithms for circular graph optimization
- Variable Neighborhood Search - Enhancing VNS methodologies for complex optimization scenarios
Affiliations
- GRAFO Research Group - Group for Research in Algorithms For Optimization, Universidad Rey Juan Carlos
- Universidad Internacional Menéndez Pelayo - Master’s program in Artificial Intelligence Research
Interests
Artificial Intelligence | Metaheuristics | Heuristics | Optimization | Graph Theory | Combinatorial Optimization
