Nivel SNII:1
Formación:
Doctorado en Ciencias en Computación (CINVESTAV-IPN)
Áreas de interés:
- Optimización multi-objetivo utilizando algoritmos evolutivos y técnicas de programación matemática
- Búsqueda de arquitecturas neuronales para restauración de imágenes y tareas de procesamiento de lenguaje natural
- Modelos de lenguaje generativo locales aplicados a la salud, nutrición y temáticas sociales
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Tesis:
- An Evolutionary Algorithm for the numerical treatment of Equality Constrained Multi-Objective Optimisation Problems, Jesús Leopoldo Llano García, Maestría en Ciencias Computacionales, ITESM-CEM, 2020.
- Portfolio Selection using Artificial Intelligence Techniques in the Mexican Stock Exchange, Samuel Guadalupe Rodríguez Rodríguez, Maestría en Ciencias Computacionales, ITESM-MTY, 2022.
- The Use Of Evolutionary Algorithms To Tackle The Energy Economy Parameter-Dependent Multi-Objective Optimization Problem In Fuel-Cell Hybrid Electric Vehicles, Luis Fernando Sánchez Spínola, Maestría en Ciencias Computacionales, ITESM-CEM, 2023.
- The Use of Evolutionary Algorithms for the Design of Lithium-Ion Battery Packs and Battery Cells, César Alejandro Rodríguez Montoya, Maestría en Ciencias Computacionales, ITESM-CEM, 2023.
- An improved Multi-objective Optimization problem model for enhancing UAV Path Planning, Franco Castañon Guerrero, Maestría en Ciencias Computacionales, ITESM-CEM, 2024.
- Optimization of Kinetic and Operating Parameters in Bioreactors Using Evolutionary Algorithms, Gonzalo Irving Barrera Hernández, Maestría en Ciencias Computacionales, ITESM-CEM, 2024.
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Publicaciones:
- Neural architecture search for image super-resolution: A review on the emerging state-of-the-art, JLL García, R Monroy, VAS Hernández, Neurocomputing 610, 128481
- Surrogate Modeling for Efficient Evolutionary Multi-Objective Neural Architecture Search in Super Resolution Image Restoration , S Sarmiento-Rosales, JLL Garcia, JG Falcón-Cardona, R Monroy, Manuel Iván Casillas del Llano, Victor Adrián Sosa Hernández, In Proceedings of the 16th International Joint Conference on Computational Intelligence (IJCCI 2024), pages 242-249
- The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems, H Wang, M Emmerich, A Deutz, VAS Hernández, O Schütze, Mathematical and Computational Applications 28 (1), 10
- An Experimental Protocol for Neural Architecture Search in Super-Resolution, JLL García, R Monroy, VAS Hernández, Proceedings of the IEEE/CVF International Conference on Computer Vision
- Severity of SARS-CoV-2 infection is linked to double-negative (CD27− IgD−) B cell subset numbers, R Cervantes-Díaz, VA Sosa-Hernández, J Torres-Ruíz, Inflammation Research, 1-10
- COARSE-EMOA: An indicator-based evolutionary algorithm for solving equality-constrained multi-objective optimization problems, JLL García, R Monroy, VAS Hernández, CAC Coello, Swarm and Evolutionary Computation 67, 100983
- A practical tutorial for decision tree induction: Evaluation measures for candidate splits and opportunities, VAS Hernandez, R Monroy, MA Medina-Pérez, O Loyola-Gonzalez, Francisco Herrera, ACM Computing Surveys (CSUR) 54 (1), 1-38
- On the choice of neighborhood sampling to build effective search operators for constrained MOPs, A Lara, L Uribe, S Alvarado, VA Sosa, H Wang, O Schütze, Memetic Computing 11, 155-173
- The set-based hypervolume Newton method for bi-objective optimization, VAS Hernández, O Schütze, H Wang, A Deutz, M Emmerich, IEEE transactions on cybernetics 50 (5), 2186-2196
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Datos de contacto: vsosa@tec.mx