CS
The Computer Science area of CIMAT is made up of a group of leading researchers at a national and international level in their work oriented towards research, teaching, training and technological development. The area carries out research on the following main topics:
Signal, image and computer vision processing
The Signal Processing and Computer Vision research line has four research areas: Signal and Image Processing and Analysis, Medical Image Processing, Computer Vision and Multimedia Transmission...
Investigadoras e Investigadores Titulares
Investigadoras e Investigadores Asociados
Investigadoras e Investigadores por México
Post-Doctorantes
Organización desde hace 25 años de la Reunión de Neuroimágenes y Visión Computacional NeuroVisión junto con el Instituto de Neurobiología de la UNAM. Esta reunión es la más importante en el país, ya que conjunta métodos de visión computacional y aplicaciones en imágenes médicas.
Pat-Chan, A. E., Hernandez-Lopez, F. J., & Moreno-Sabido, M. R. (2023). Seguimiento de objetos en video mediante el método de emparejamiento de bloques. Research in Computing Science, 152(8), pp. 21-33. ISSN: 1870-4069 Latindex. 1er lugar en el premio al mejor poster del COMIA-2023.
Martínez-López, J. A., De-la-Torre-Gutierrez, H., & Hernandez-Lopez, F. J. (2023). Detección de antiespacios urbanos usando YOLO: caso de estudio Mexicali. Research in Computing Science, 152(9), pp. 21-33. ISSN: 1870-4069 Latindex. 3er lugar en los premios a los mejores artículos del COMIA-2023.
Se organiza el Seminario de Matemáticas Aplicadas y Computación (SMAC) de forma conjunta con Facultad de Matemáticas de la UADY, el cual sesiona cada 15 días invitando a estudiantes e investigadores a compartir sus conocimientos con el fin de dar a conocer sus respectivos trabajos de investigación y crear nuevas colaboraciones.
El equipo liderado por investigadors de CIMAT (Alonso Ramírez-Manzanares, José L. Marroquín, Mariano Rivera et. al.) ganó el primer lugar en modelación computacional en el workshop White Matter Modelling Challenge dentro del International Symposium of Biomedical Imaging 2015 llevado a cabo en la ciudad de NY, EU. El título del trabajo es “Empirical Diffusion-and-Direction Distributions (ED^3) to Estimate White Matter Microstructure”.
PRONACES: 321075 “Movilidad urbana rural integrada e innovación en electromovilidad en Yucatán” de la convocatoria 2021-2024 Proyectos nacionales de investigación e incidencia para transitar a un sistema energético social y ambientalmente sustentable. Universidad Modelo. 2022-Actualmente. Participación como colaborador con el Laboratorio Urbano de la Universidad Modelo. Responsable del proyecto: Dr. Alfredo Arias Trinidad de la Escuela de Ingeniería de la Universidad Modelo. Logros: Dos tesis de maestría en proceso, una de la maestría en Cómputo Estadístico del CIMAT-Monterrey y otra de la maestría en Ciencias de la Computación y Matemáticas Industriales del CIMAT-Guanajuato.
Análisis de sistemas de flujo urbano para el diseño de ciudades inteligentes de la convocatoria de apoyo a la investigación científica y tecnológica 2019 de Institutos Tecnológicos Federales y Centros. Modalidad Posgrado PNPC. Instituto Tecnológico de Mérida. Ene-Dic/2019. Participación como colaborador. Logros: Codirector de tesis de dos alumnos de maestría del ITM, “Estimación de tráfico vehicular en capturas de video aéreo” y “Reconocimiento de señales de tránsito utilizando redes neuronales artificiales y realidad aumentada”.
Participación institucional en el subproyecto “Detección satelital de Sargazo en Imágenes de Radar de Apertura Sintética”, dentro del proyecto denominado “Sistemas de Observación y Alerta Temprana del Sargazo (Proyecto Piloto)”, apoyado por los Programas Nacionales Estratégicos de Ciencia, Tecnología y Vinculación con los sectores Social, Público y Privado del CONACyT, No. Proyecto 321367, 2022.
Machine learning and data analysis
Under construction…
Numerical methods, parallel computing and optimization
In the modeling, optimization, and parallel computing group, we focus on developing computational methods applicable to solving problems in engineering, physics, logistics and planning, among other areas. We are specialists in different methodologies involved in this type of problem, including system modeling, generally through differential equations, and optimization methods, including both classical and heuristic methods.
Nowadays, many problems requiring modeling and optimization use large amounts of data and computation. Our group deals with such issues by using parallel computing through the high-performance computing laboratories at CIMAT. We are experts in the development of parallel algorithms, including shared and distributed memory systems and GPUs.
One of the defining characteristics of our research group at CIMAT is our commitment to innovation. We don't just rely on existing libraries for application development; we pioneer new techniques for simulation and optimization. This often leads to creating our own software and developing efficient and effective algorithms. As a result, we are also involved in developing algorithms and data structures that can be implemented efficiently and harness the power of recent hardware.
In the optimization area, research is carried out in both single-objective and multi-objective optimization, using stochastic optimization techniques such as evolutionary algorithms, memetic algorithms, estimation of distribution algorithms, among others. We also develop mathematical programming techniques and gradient methods. Both are applied to global and constrained design and optimization problems that arise in various fields, such as logistics, cryptography, or civil engineering. Through establishing teams with students interested in these topics, we have a tradition of participating in optimization contests to validate and show the advantages of the innovations made in this area. Such aspects promote the group's visibility, resulting in various international awards.
In the modeling area, numerical solution models of partial differential equations are studied and developed using Finite Elements, Finite Volume, Finite Differences, and, recently, Discrete Exterior Calculus (DEC). These techniques are used to solve problems in engineering applications. Studies are carried out on fuel cell design, thermal modeling in solids, modeling of fluids in physical systems, design of complex structures in civil engineering, development of new materials, biological material applications, and numerical modeling of groundwater and floods.
In parallel computing, we work on different parallelization technologies and paradigms, such as OpenMP, MPI, and CUDA, applying these tools to the parallelization of modeling and optimization algorithms. We are specialists in the efficient use of this type of hardware and offer consulting and training services.
The members of this group collaborate with various research groups from numerous national and international institutions. Some of the institutions with which we have collaborated are the following: CIMNE, University of La Laguna and University of Málaga, in Spain, Napier University, in Scotland, University of Leipzig, in Germany, University of Guanajuato, Autonomous University of Zacatecas , Universidad Michoacana San Nicolás de Hidalgo ITESM, CINVESTAV, CentroGeo, CICESE, ITAM, Instituto Tecnológico de Mérida, Universidad Autónoma de Yucatán, and CICY, in Mexico. Through these collaborations, it is possible to expand the set of problems and techniques available to the team and develop multidisciplinary teams to address the problems.
Senior Researchers
Associate Researchers
Researchers for Mexico
Post-Doctorates
Robotics and Intelligent Systems
The Robotics and Intelligent Systems (RSI by its acronym in Spanish) group at CIMAT has more than 15 years of experience conducting research in mobile robotics. Its theoretical approach, which transcends the practical, has made the CIMAT RSI group position itself as a reference within the robotics community in Mexico. The research works of its members are constantly published in the most important forums in the area, such as the IEEE Transactions on Robotics (IEEE TRO), International Journal of Robotics Research (IJRR), IEEE Robotics and automation Letters (IEEE RAL), Robotics and Autonomous Systems (RAS), Autonomous Robots (AURO), Automatica, ISA Transactions, IEEE Transactions on Control Systems Technology, Journal of the Franklin Institute, Control Engineering Practice, IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Affective Computing, Virtual Reality, IEEE International Conference on Robotics and Automation (ICRA), International Workshop on the Algorithmic Foundations of Robotics (WAFR), International Conference on Intelligent Robots and Systems (IROS), among others.
The group is made up of twelve permanent members, all of them in the National System of Researchers (SNII by its acronym in Spanish) – one researcher with level 3, four with level 2, five with level 1, and two with candidate level. The research lines of the area focus globally on motion planning, control theory, perception, uncertainty modeling, and the integration of these different levels of estimation and decision through coherent and effective feedback schemes. More specifically, the most recent lines of research in the area have addressed problems through techniques such as optimal control, nonlinear control with sensory feedback, model predictive control, consensus-based distributed control, visual servo control, partially observable Markov decision processes, generative prediction models, Bayesian and combinatorial filtering, computational geometry, sampling-based planning methods, among others. The range of applications of the research covers ground and aerial robots, e.g. object search and reconstruction, exploration of unknown environments, multi-robot formations, pursuit/evasion, humanoid locomotion, autonomous cars and virtual reality.
The research group currently maintains international collaborations with Georgia Tech, U. de Sherbrooke, LAAS-CNRS, INRIA, U. of Oulu, Université de Technologie de Compiègne, U. de Zaragoza and national collaborations with Intel Labs Guadalajara, CINVESTAV Saltillo and Guadalajara, INAOE, CICESE, CIO Ags. and the U. of Guanajuato.
Investigadoras e Investigadores Titulares
Investigadoras e Investigadores Asociados
Investigadoras e Investigadores por México
Post-Doctorantes
Postgraduate in
Computer
Science
Master of
Science with
orientation in
Robotics
Zacatecas Unit
Master in
Software
Engineering
Zacatecas Unit
Coordinator of the Computer Science Area
E-mail: dalmau@cimat.mx
Graduate Coordinator Computer Science Area
E-mail: alram@cimat.mx
