Cosijopii Garcia-Garcia

Cosijopii Garcia Garcia is a researcher in the field of Evolutionary Computation. He is currently pursuing a PhD at INAOE, where his research focuses on Multi-Objective Optimization Problems (MOPs) and Multi-Objective Neural Architecture Search (NAS), as well as Cellular approaches for parallelized Genetic Algorithms in MOPs.

Cosijopii has experience in using optimization techniques such as Genetic Algorithms (GA), Genetic Programming (GP), Cartesian Genetic Programming (CGP), and Differential Evolution (DE), as well as metaheuristics like Particle Swarm Optimization (PSO) to solve complex problems.

He also possesses a strong background in Machine Learning (ML) and Deep Learning, which enables him to apply these techniques to solve real-world problems in a variety of domains. Cosijopii’s research interests include constrained optimization, multi-objective optimization, and optimization in machine learning. He has published several papers in top-tier conferences and journals.