Camilo Chacón Sartori
I'm a Ph.D. candidate in Artificial Intelligence at the Artificial Intelligence Research Institute (IIIA-CSIC) in Bellaterra, Spain currently working on the intersection of computational optimization, metaheuristics, and large language models. I previously did research focused on developing visualization tools like STNWeb for analyzing optimization algorithms, working with researchers like Christian Blum and Gabriela Ochoa.
My work focuses on establishing novel connections between traditional optimization methods and modern AI approaches, particularly in developing hybrid systems that leverage large language models to enhance metaheuristic algorithms. I'm especially interested in creating visualization tools and automated analysis systems that make complex optimization algorithms more interpretable and accessible.
A key aspect of my research involves exploring how LLMs can be integrated with optimization techniques to improve algorithm performance and analysis. I've published several papers demonstrating innovative approaches like using LLMs for pattern recognition in metaheuristics and developing benchmark generators for assessing variability in graph analysis. Through my work, I aim to bridge the gap between classical optimization methods and cutting-edge AI technologies while making these tools more accessible to the broader research community.
My work focuses on establishing novel connections between traditional optimization methods and modern AI approaches, particularly in developing hybrid systems that leverage large language models to enhance metaheuristic algorithms. I'm especially interested in creating visualization tools and automated analysis systems that make complex optimization algorithms more interpretable and accessible.
A key aspect of my research involves exploring how LLMs can be integrated with optimization techniques to improve algorithm performance and analysis. I've published several papers demonstrating innovative approaches like using LLMs for pattern recognition in metaheuristics and developing benchmark generators for assessing variability in graph analysis. Through my work, I aim to bridge the gap between classical optimization methods and cutting-edge AI technologies while making these tools more accessible to the broader research community.
Publications
VisGraphVar: A benchmark generator for Assessing Variability in Graph Analysis Using Large Vision-Language Models
Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa
IEEE Access 2025
An Extension of STNWeb Functionality: On the Use of Hierarchical Agglomerative Clustering as an Advanced Search Space Partitioning Strategy
Camilo Chacón Sartori, Christian Blum, Gabriela Ochoa
Annual Conference on Genetic and Evolutionary Computation 2024
Q-Learning Ant Colony Optimization supported by Deep Learning for Target Set Selection
Jairo Enrique Ramírez Sánchez, Camilo Chacón Sartori, C. Blum
Annual Conference on Genetic and Evolutionary Computation 2023
Search Trajectory Networks Meet the Web: A Web Application for the Visual Comparison of Optimization Algorithms
Camilo Chacón Sartori, C. Blum, G. Ochoa
International Conference on Software and Computer Applications 2023
STNWeb for the Analysis of Optimization Algorithms: A Short Introduction
Camilo Chacón Sartori, Christian Blum
Modeling, Identification and Control 2024