Dr.Jorge de Jesús Gálvez Rodríguez

RESEÑA

El Dr.  Gálvez se tituló de la Licenciatura en Informática y de la Licenciatura en Ingeniería en Computación en la Universidad de Guadalajara. Obtuvo el título de Maestro y Doctor en Ciencias en Ingeniería Electrónica y Computación en la Universidad de Guadalajara.

Actualmente es profesor en la División de Electrónica y Computación en el Centro Universitario de Ciencias Exactas e Ingenierías de la Universidad de Guadalajara. Además, es miembro del Colegio de Profesionistas en Sistemas de Información de Jalisco. Asi mismo, el Dr. Gálvez pertenece a la linea de investigación de Internet de las cosas y Cómputo en la nube.

FORMACIÓN ACADÉMICA

• Rodríguez, A., Pérez-Cisneros, M., Rosas-Caro, J.C., ...Gálvez, J., Cuevas, E. (2021). Robust clustering routing method for wireless sensor networks considering the locust search scheme. Energies. 14(11),3019.
  • ​https://doi.org/10.3390/en14113019
• Ray, S., Das, A., Dhal, K.G., Gálvez, J., Naskar, P.K. (2021). Cauchy with whale optimizer based eagle strategy for multi-level color hematology image segmentation. Neural Computing and Applications. (33) 5917-5949.
  • https://doi.org/10.1007/s00521-020-05368-7​
• Dhal, K.G., Das, A., Ray, S., Gálvez, J., Das, S. (2021). Histogram Equalization Variants as Optimization Problems: A Review. Archives of Computational Methods in Engineering (28) 1471-1496.
  • https://doi.org/10.1007/s11831-020-09425-1​
• Dhal, K.G., Das, A., Ray, S., Gálvez, J. (2021) Randomly Attracted Rough Firefly Algorithm for histogram based fuzzy image clustering. Knowledge-Based Systems. (216) 106814.
  • https://doi.org/10.1016/j.knosys.2021.106814
• Cuevas, E., Gálvez, J., Avalos, O., Chavarin, Á. (2021). A mean shift segmentation scheme using several pixel characteristics. Computers and Electrical Engineering (90), 107022.
  • https://doi.org/10.1016/j.compeleceng.2021.107022
• Avalos, O., Cuevas, E., Becerra, H.G., ...Hinojosa, S., Zaldívar, D. (2021). Kernel Recursive Least Square Approach for Power System Harmonic Estimation. Electric Power Components and Systems. 48(16-17), 1708-1721.
  • https://doi.org/10.1080/15325008.2021.1908457
• Cuevas, E., Gálvez, J., Avila, K., Toski, M., Rafe, V. (2020).A new metaheuristic approach based on agent systems principles. Journal of Computational Science, 47, 101244
  • https://doi.org/10.1016/j.jocs.2020.101244
• Dhal, K.G., Das, A., Gálvez, J., Ray, S., Das, S. (2020). An Overview on Nature-Inspired Optimization Algorithms and Their Possible Application in Image Processing Domain. Pattern Recognition and Image Analysis, 30(4) 614- 631.
  • https://doi.org/10.1134/S1054661820040100
• Avalos, O., Cuevas, E., Gálvez, J., Houssein, E.H., Hussain, K. (2020). Comparison of circular symmetric low-pass digital IIR filter design using evolutionary computation techniques. Mathematics, 8(8) 1226. 
  • https://doi.org/10.3390/math8081226

• Gálvez, J., Cuevas, E., Becerra, H., & Avalos, O. (2019). A hybrid optimization approach based on clustering and chaotic sequences. International Journal of Machine Learning and Cybernetics, 1-43.
• Dhal, K. G., Gálvez, J., Ray, S., Das, A., & Das, S. (2020). Acute lymphoblastic leukemia image segmentation driven by stochastic fractal search. Multimedia Tools and Applications, 1-29.
• Cuevas, E., & Galvez, J. (2019). An optimization algorithm guided by a machine learning approach. International Journal of Machine Learning and Cybernetics, 10(11), 2963-2991.
• Dhal, K. G., Ray, S., Das, A., Gálvez, J., & Das, S. (2019). Fuzzy Multi-level Color Satellite Image Segmentation Using Nature-Inspired Optimizers: A Comparative Study. Journal of the Indian Society of Remote Sensing, 47(8), 1391-1415.
• Gálvez, J., Cuevas, E., Hinojosa, S., Avalos, O., & Pérez-Cisneros, M. (2019). A reactive model based on neighborhood consensus for continuous optimization. Expert Systems with Applications, 121, 115-141.
• Dhal, K. G., Gálvez, J., & Das, S. (2019). Toward the modification of flower pollination algorithm in clustering-based image segmentation. Neural Computing and Applications, 1-19.
• Dhal, K. G., Das, A., Ray, S., Gálvez, J., & Das, S. (2019). Nature-inspired optimization algorithms and their application in multi-thresholding image segmentation. Archives of Computational Methods in Engineering, 1-34.
• Avalos, O., Cuevas Jimenez, E. V., Valdivia-González, A., Gálvez, J., Hinojosa, S., Zaldívar, D., & Oliva, D. (2019). A Comparative Study of Evolutionary Computation Techniques for Solar Cells Parameter Estimation. Computación y Sistemas, 23(1), 231.
• Hinojosa, S., Avalos, O., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Gálvez, J. (2018). Unassisted thresholding based on multi-objective evolutionary algorithms. Knowledge-Based Systems, 159, 221-232.
• Gálvez, J., Cuevas, E., Avalos, O., Oliva, D., & Hinojosa, S. (2018). Electromagnetism-like mechanism with collective animal behavior for multimodal optimization. Applied Intelligence, 48(9), 2580-2612.
• Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2018). Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm. Neural Computing and Applications, 29(8), 319-335.
• Díaz, P., Pérez-Cisneros, M., Cuevas, E., Avalos, O., Gálvez, J., Hinojosa, S., & Zaldivar, D. (2018). An improved crow search algorithm applied to energy problems. Energies, 11(3), 571.
• Díaz-Cortés, M. A., Cuevas, E., Gálvez, J., & Camarena, O. (2017). A new metaheuristic optimization methodology based on fuzzy logic. Applied Soft Computing, 61, 549-569.
• Oliva, D., Hinojosa, S., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2017). Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm. Expert Systems with Applications, 79, 164-180.
• Cuevas, E., Gálvez, J., & Avalos, O. (2017). Parameter estimation for chaotic fractional systems by using the locust search algorithm. Computación y Sistemas, 21(2), 369-380.
• Gálvez, J., Cuevas, E., & Avalos, O. (2017). Flower pollination algorithm for multimodal optimization. International Journal of Computational Intelligence Systems, 10(1), 627-646.
• Avalos, O., Cuevas, E., & Gálvez, J. (2016). Induction motor parameter identification using a gravitational search algorithm. Computers, 5(2), 6.
• Cuevas, E., Gálvez, J., Hinojosa, S., Avalos, O., Zaldívar, D., & Pérez-Cisneros, M. (2014). A comparison of evolutionary computation techniques for IIR model identification. Journal of Applied Mathematics, 2014.

LIBROS

• Cuevas, E., Gálvez, J., & Avalos, O. (2019). Recent Metaheuristics Algorithms for Parameter Identification. Springer Nature.

PARTICIPACIONES EN CONGRESOS

• Hinojosa, S., Avalos, O., Gálvez, J., Oliva, D., Cuevas, E., & Pérez-Cisneros, M. (2018, November). Remote sensing imagery segmentation based on multi-objective optimization algorithms. In 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.

Knowledge-Based Systems