MCI Publicaciones Investigadores – Tecnológico Nacional de México – Tijuana
Tecnológico Nacional de México – Tijuana >MCI Publicaciones Investigadores

MCI Publicaciones Investigadores

  • Cárdenas-Valdez, J. R., Ramírez-Villalobos, R., Ramirez-Ubieta, C., & Inzunza-Gonzalez, E. (2024). Enhancing Security of Telemedicine Data: A Multi-Scroll Chaotic System for ECG Signal Encryption and RF Transmission. Entropy, 26(9), 787.
  • Galarza-Falfan, J., García-Guerrero, E. E., Aguirre-Castro, O. A., López-Bonilla, O. R., Tamayo-Pérez, U. J., Cárdenas-Valdez, J. R., … & Inzunza-Gonzalez, E. (2024). Path planning for autonomous mobile robot using intelligent algorithms. Technologies, 12(6), 82.
  • Cárdenas-Valdez, J. R., Ramírez-Arzate, F., Corral-Domínguez, A. H., Hurtado-Sánchez, C., Calvillo-Téllez, A., & García-Guerrero, E. E. (2023). Development of an Adaptive Acquisition and Transmission System for Digital Processing of ECG Signals under Variable n-QAM Schemes. Revista mexicana de ingeniería biomédica, 44(SPE1), 117-127.
  • Trujillo-Toledo, D. A., López-Bonilla, O. R., García-Guerrero, E. E., Esqueda-Elizondo, J. J., Cárdenas-Valdez, J. R., Tamayo-Pérez, U. J., … & Inzunza-González, E. (2023). Real-time medical image encryption for H-IoT applications using improved sequences from chaotic maps. Integration, 90, 131-145.
  • Cárdenas-Valdez, J. R., Galaviz-Aguilar, J. A., Vargas-Rosales, C., Inzunza-González, E., & Flores-Hernández, L. (2022). A Crest Factor Reduction Technique for LTE Signals with Target Relaxation in Power Amplifier Linearization. Sensors, 22(3), 1176.
  • Galaviz-Aguilar, J. A., Vargas-Rosales, C., Cárdenas-Valdez, J. R., Aguila-Torres, D. S., & Flores-Hernández, L. (2022). A Comparison of Surrogate Behavioral Models for Power Amplifier Linearization under High Sparse Data. Sensors, 22(19), 7461.
  • Galaviz-Aguilar, J. A., Vargas-Rosales, C., Aguila-Torres, D. S., & Cárdenas-Valdez, J. R. (2024). Power Amplifier Modeling Comparison for Highly and Sparse Nonlinear Behavior Based on Regression Tree, Random Forest, and CNN for Wideband Systems. In Machine Learning for Complex and Unmanned Systems (pp. 57-75). CRC Press.
  • Carmona-Troyo, J. A., Trujillo, L., Enríquez-Zárate, J., Hernandez, D. E., & Cárdenas-Florido, L. A. (2025). Classification of damage on wind turbine blades using automatic machine learning and pressure coefficient. Expert Systems, 42(4). doi:10.1111/exsy.70024
  • Jose Manuel Muñoz Contreras, Leonardo Trujillo, Daniel E. Hernandez, Luis A. Cardenas Florido (2025). Benchmarking GSGP: Still competitive 10 years later?  accepted to appear in Genetic Programming and Evolvable Machines (Springer).
  • Victor Manuel Vargas-Forero, Diego Fernando Manotas Duque, Leonardo Trujillo. Comparative Study of Forecasting Methods to Predict the Energy Demand for the Market of Colombia. International Journal of Energy Economics and Policy 15 (1), 2025
  • Ramos-Rivera, D., Díaz-Ramírez, A., Trujillo, L., García-Vázquez, J. P. ., & Mejía-Álvarez, P. (2024). Classification of wandering patterns in the elderly using  machine learning and time series analysis. IEEE Latin America Transactions, 22(12), 1009–1018.
  • Spector, L., & Trujillo, L. (2024). Chief editorship transition. In Genetic Programming and Evolvable Machines (Vol. 25, Issue 2). Springer Science and Business Media LLC.
  • Yazmin Maldonado , Ruben Salas, Joel A. Quevedo, Rogelio Valdez, Leonardo Trujillo. GSGP-Hardware: Instantaneous Symbolic Regression with an FPGA Implementation of Geometric Semantic Genetic Programming, accepted to appear in Genetic Programming and Evolvable Machines (Springer), 2024
  • L. Trujillo, D. E. Hernandez, A. Rodriguez, O. Monroy, and O. Villanueva, “Effects of feature reduction on emotion recognition using EEG signals and machine learning,” Expert Systems. Wiley, Mar. 25, 2024.
  • Cárdenas Florido L, Trujillo L, Hernandez DE, Muñoz Contreras JM. M5GP: Parallel Multidimensional Genetic Programming with Multidimensional Populations for Symbolic Regression. Mathematical and Computational Applications. 2024; 29(2):25.
  • Illya Bakurov, José Manuel Muñoz Contreras, Mauro Castelli, Nuno Rodrigues, Sara Silva, Leonardo Trujillo, Leonardo Vanneschi. Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs, accepted to appear in Genetic Programming and Evolvable Machines (Springer), 2024
  • Jakobović, D., Medvet, E., Pappa, G. L., & Trujillo, L. (2023). Introduction to special issue on highlights of genetic programming 2022 events. In Genetic Programming and Evolvable Machines (Vol. 25, Issue 1).
  • Enríquez-Zárate, J, Gómez-Peñate, S, Hernández, C, Villarreal-Valderrama, F, Velázquez, R, Trujillo, L. Optimization of vibration control using a hybrid scheme with sliding-mode and positive position feedback. Optim Control Appl Meth. 2023; 1-15.
  • Vanneschi, L., Trujillo, L. Introduction to the peer commentary special section on “Jaws 30” by W. B. Langdon. Genet Program Evolvable Mach 24, 18 (2023).
  • Quiroz-Castellanos M, de la Fraga LG, Lara A, Trujillo L, Schütze O. Numerical and Evolutionary Optimization 2021. Mathematical and Computational Applications. 2023; 28(3):71.
  • Rodríguez, D.A., Diaz-Escobar, J., Díaz-Ramírez, A., Trujillo, L.. Domain-adaptive pre-training on a BERT model for the automatic detection of misogynistic tweets in Spanish. Soc. Netw. Anal. Min. 13, 126 (2023).
  • Trujillo, L., Nation, J., Muñoz, L., & Galván, E. (2023). Predicting the success of transfer learning for genetic programming using DeepInsight feature space alignment. In AI Communications (pp. 1–15). IOS Press.
  • Naredo E, Sansores C, Godinez F, López F, Urbano P, Trujillo L, Ryan C. Comprehensive Analysis of Learning Cases in an Autonomous Navigation Task for the Evolution of General Controllers. Mathematical and Computational Applications. 2023; 28(2):35.
  • Trujillo, L., Hu, T., Lourenço, N. anmd Zhang, M, Editorial Introduction. Genet Program Evolvable Mach (2022). (SI Highlights of Genetic Programming Eventos in 2021)
  • Cristian Sandoval, Oliver Cuate, Luis C. González, Leonardo Trujillo, Oliver Schütze. Towards fast approximations for the hypervolume indicator for multi-objective optimization problems by Genetic Programming, Applied Soft Computing, 2022, 109103, ISSN 1568-4946.
  • Leonardo Trujillo, Jose Manuel Muñoz Contreras, Daniel Hernandez, Mauro Castelli, Juan J.Tapia. GSGP-CUDA — A CUDA framework for Geometric Semantic Genetic Programming in SoftwareX, Volume 18, June 2022, 101085.
  • J. C. Dibene, Y. Maldonado, L. Trujillo and E. Dunn, "Prepare for Ludicrous Speed: Marker-based Instantaneous Binocular Rolling Shutter Localization," in IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2022.3150485.
  • Enríquez Zárate, Josué, María d.l.Á. Gómez López, Javier A. Carmona Troyo, and Leonardo Trujillo. 2022. "Analysis and Detection of Erosion in Wind Turbine Blades" Mathematical and Computational Applications 27, no. 1:5.
  • Cerrada, Mariela, Leonardo Trujillo, Daniel E. Hernández, Horacio A. Correa Zevallos, Jean C. Macancela, Diego Cabrera, and René Vinicio Sánchez. 2022. "AutoML for Feature Selection and Model Tuning Applied to Fault Severity Diagnosis in Spur Gearboxes" Mathematical and Computational Applications 27, no. 1: 6.
  • Edgar Galván, Leonardo Trujillo, Fergal Stapleton, Semantics in Multi-objective Genetic Programming, Applied Soft Computing, V. 115, 2022, p. 108143.
  • Torres, N., Trujillo, L., Maldonado, Y., & Vera, C. (2021). Correction of the Travel Time Estimation for Ambulances of the Red Cross Tijuana using Machine Learning. Computers in Biology and Medicine, 104798.
  • Rodriguez, D. A., Diaz-Ramirez, A., Miranda-Vega, J. E., Trujillo, L., & Mejia-Alvarez, P. (2021). A Systematic Review of Computer Science Solutions for Addressing Violence Against Women and Children. IEEE Access, 9, 114622–114639.
  • Trujillo, L., Villanueva, O.M. and Hernandez, D.E. 2021. A Novel Approach For Search-Based Program Repair. IEEE Software. 38, 4 (Jul. 2021), 36–42.
  • Z-Flores, E.; Trujillo, L.; Legrand, P.; Faïta-Aïnseba, F. EEG Feature Extraction Using Genetic Programming for the Classification of Mental States. Algorithms 2020, 13, 221
  • Víctor R. López‐López, Lizbeth Escobedo, Leonardo Trujillo. Towards an automatic coding of observational studies: Coding neurofeedback therapies of children with autism, accepted to appear in Expert Systems (2020).
  • Josué Zárate, Perla Juárez-Smith, Javier Carmona, Leonardo Trujillo and Salvador de Lara. Modeling the vibration response of a gas turbine using machine learning, accepted to appear in Expert Systems (2020).
  • Leonardo Trujillo, Uriel López, Pierrick Legrand. SOAP: Semantic Outliers Automatic Preprocessing, accepted to appear in Information Sciences (2020).
  • Esparcia-Alcázar, A.I., Trujillo, L. Special Issue on Integrating numerical optimization methods with genetic programming. Genet Program Evolvable Mach (2020).
  • Leonardo Trujillo, Ernesto Álvarez González, Edgar Galván, Juan J. Tapia, Antonin Ponsich. On the Analysis of Hyper-Parameter Space for a Genetic Programming System with Iterated F-Race, accepted to appear in Soft Computing (2020).
  • Darian Reyes Fernández de Bulnes, Yazmin Maldonado, Leonardo Trujillo. Development of multi- objective High-Level Synthesis for FPGAs, accepted to appear in Scientific Programming (2020).
  • Leonardo Trujillo, Guadalupe Alvarez-Hernandez, Yazmin Maldonado, Carlos Vera, Comparative analysis of relocation strategies for ambulances in the city of Tijuana, Mexico, accepted to appear in Computers in Biology and Medicine (2019).
  • Yolocuauhtli Salazar-Muñoz, Angelina G. López-Pérez, Blanca E. García-Caballero, Refugio Muñoz- Rios, Luis Ruano-Calderón and Leonardo Trujillo. Classification and assessment of the patelar reflex response through biomechanical measures, accepted to appear in Journal of Healthcare Engineering, 2019
  • Perla Juárez-Smith, Leonardo Trujillo, Mario García-Valdez, Francisco Fernández de Vega, Francisco Chávez. Local Search in Speciation-based Bloat Control for Genetic Programming, accepted to appear in Genetic Programming and Evolvable Machines, 2019.
  • José Alejandro Galaviz-Aguilar, Patrick Roblin, José Ricardo Cárdenas-Valdez, Emigdio Z-Flores, Leonardo Trujillo, José Cruz Nuñez-Pérez, and Oliver Schütze. 2019. Comparison of a genetic programming approach with ANFIS for power amplifier behavioral modeling and FPGA implementation. Soft Comput. 23, 7 (April 2019), 2463-2481.
  • Leonardo Vanneschi, Mauro Castelli, Kristen Scott, Leonardo Trujillo, Alignment-based genetic programming for real life applications, Swarm and Evolutionary Computation, Volume 44, 2019, 840-851
  • José Enrique Hernández, Víctor Díaz-Ramírez, Leonardo Trujillo, Pierrick Legrand. Design of estimators for restoration of images degraded by haze using genetic programming, Swarm and Evolutionary Computation, 44:49-63, 2019.
  • Muñoz, L., Trujillo, L., Silva, S., Castelli, M., Vanneschi, L. Evolving multidimensional transformations for symbolic regression with M3GP. Memetic Comp., vol. 11, no. 2, pp. 111-126, 2019.
  • Víctor R. LópezLópez, Leonardo Trujillo, Pierrick Legrand. Applying Genetic Improvement to a Genetic Programming library in C++, accepted to Soft Computing
  • J. R. López, L. C. González, J. Wahlström, M. Montes y Gómez, L. Trujillo and G. Ramírez-Alonso, A Genetic Programming Approach for Driving Score Calculation in the Context of Intelligent Transportation Systems, in IEEE Sensors Journal, vol. 18, no. 17, pp. 7183-7192, 1 Sept.1, 2018.
  • Stefano Beretta, Mauro Castelli, Luis Muñoz, Leonardo Trujillo, Yuliana Martínez, Aleš Popovič, Luciano Milanesi, and Ivan Merelli, A Scalable Genetic Programming Approach to Integrate miRNA-Target Predictions: Comparing Different Parallel Implementations of M3GP, Complexity, vol. 2018, Article ID 4963139, 13 pages, 2018
  • Leonardo Trujillo, Yazmin Maldonado, Oliver Schuetze. Editorial for Thematic Issue on Numerical and Evolutionary Optimization. Computación y Sistemas, 22(2): 313-314 (2018)
  • J Enríquez-Zárate, Leonardo Trujillo, GK Toledo-Ramírez, Ángel J Ramos-Cirilo, C Hernández Siordia. Optimization of PPF Control of a Building-like Structure for Vibration Control. Computación y Sistemas, 22(2): 413-424 (2018).
  • Torres N, Trujillo L and Maldonado Y (2018) Modeling Uncertainty for the Double Standard Model Using a Fuzzy Inference System. Front. Robot. AI 5:31.
  • López, R.; González Gurrola, L.C.; Trujillo, L.; Prieto, O.; Ramírez, G.; Posada, A.; Juárez-Smith, P.;Méndez, L. How Am I Driving? Using Genetic Programming to Generate Scoring Functions for Urban Driving Behavior. Math. Comput. Appl. 2018, 23, 19.
  • Paul Campos, Luis Coria and Leonardo Trujillo. Nonlinear speed sensorless control of a surface-mounted PMSM based on a Thau observer, accepted to appear in Electrical Engineering (2017)
  • Emigdio Z-Flores, Mohamed Abatal, Ali Bassam, Leonardo Trujillo, Perla Juárez-Smith, Youness El Hamzaoui. Modeling the Adsorption of Phenols and Nitrophenols by Activated Carbon using Genetic Programming, Journal of Cleaner Production, 161:, 860-870, 2017.
  • Mauro Castelli, Leonardo Vanneschi, Leonardo Trujillo and Aleš Popovič. Stock index return forecasting: semantics-based genetic programming with local search optimiser, Int. J. Bio-Inspired Computation, 10(3):159-171, 2017.
  • Mauro Castelli, Leonardo Trujillo, Ivo Gonçalves and Aleš Popovič. An evolutionary system for the prediction of high performance concrete strength based on semantic genetic programming, Computers and Concrete, 19(6):651- 658 (2017).
  • Darian Reyes, Yazmin Maldonado, Leonardo Trujillo. High-Level Synthesis through metaheuristics and LUTs optimization in FPGA devices, AI Communications vol. 30, no. 2, pp. 151-168, 2017.
  • Yuliana Martínez, Enrique Naredo, Leonardo Trujillo, Pierrick Legrand and Uriel López. A comparison of fitness- case sampling methods for genetic programming, Journal of Experimental & Theoretical ArtificialIntelligence, 29(6):1203-1224, 2017.
  • Mauro Castelli, Ivo Goncalves, Leonardo Trujillo and Ales Popovic. An Evolutionary System for Ozone Concentration Forecasting, Information Systems Frontiers, 19(5):1123-1132 (2017)
  • Enrique Naredo, Paulo Urbano, Leonardo Trujillo. The Training Set and Generalization in Grammatical Evolution for Autonomous Agent Navigation, Soft Comput. 21, 15 (2017), 4399-4416.
  • Francisco Chávez, Francisco Fernández-de-Vega, Daniel Lanza, Cesar Benavides, Juan Villegas, Leonardo Trujillo, Gustavo Olague, Graciela Román. Deploying Massive Runs of Evolutionary Algorithms with ECJ and Hadoop: reducing interest points required for face recognition, to appear in the International Journal of High Performance Computing Applications (2016)
  • Enrique Naredo, Miguel Aurelio Duarte-Villaseñor, Manuel de Jesús García-Ortega, Carlos E. Vázquez-López, Leonardo Trujillo and Oscar S. Siordia. Novelty Search for the Synthesis of Current Followers, Computación y Sistemas, 20(4): 608-621 (2016).
  • Víctor R. López-López, Leonardo Trujillo, Pierrick Legrand, Victor H. Díaz-Ramírez and Gustavo Olague. A comparison of local feature extraction paradigms applied to visual SLAM, Computación y Sistemas, 20(4):565-588 (2016).
  • Enrique Naredo, Leonardo Trujillo, Pierrick Legrand, Sara Silva, Luis Muñoz. Evolving Genetic Programming Classifiers with Novelty Search, Information Sciences, 369:347-367 (2016)
  • Emigdio Z-Flores, Leonardo Trujillo, Arturo Sotelo, Pierrick Legrand and Luis Coria. Regularity and Matching Pursuit Feature Extraction for the Detection of Epileptic Seizures, Journal of Neuroscience Methods, 266:107–125 (2016).
  • Yuliana Martínnez, Leonardo Trujillo, Pierrick Legrand and Edgar Galván-López. Prediction of Expected Performance for a Genetic Programming Classifier, Genet Program Evolvable Mach (2016) 17: 409-449 (2016)
  • Mauro Castelli, Raul Sormani, Leonardo Trujillo and Ales Popovic. Predicting Per Capita Violent Crimes in Urban Areas: an Artificial Intelligence Approach, Journal of Ambient Intelligence and Humanized Computing, 8(1):29-36 (2017)
  • Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi, and Aleš Popovič. 2016. Prediction of relative position of CT slices using a computational intelligence system. Appl. Soft Comput. 46, C (September 2016), 537- 542.
  • Josúe Zárate, Leonardo Trujillo, Salvador de Lara, Mauro Castelli, Emigdio Z-Flores, Luis Muñoz, Ales Popovic. Automatic Modeling of a Gas Turbine using Genetic Programming: An Experimental Study, Applied Soft Computing, 50:212-222 (2017)
  • Juan Carlos Dibene, Yazmin Maldonado, Carlos Vera, Mauricio de Oliveira, Leonardo Trujillo, Oliver Schütze, Optimizing the location of ambulances in Tijuana, Mexico, Computers in Biology and Medicine, 80(1):107-115 (2017).
  • Leonardo Trujillo, Luis Muñoz, Edgar Galván-López, Sara Silva. neat Genetic Programming: Controlling Bloat Naturally, Information Sciences 333:21-43 (2016).
  • Leonardo Trujillo. Book Review: Kenneth O. Stanley and Joel Lehman Why Greatness Cannot Be Planned – The Myth of the Objective Springer, 2015, Softcover ISBN 978-3-319-15523-4, to appear in Genetic Programming and Evolvable Machines.
  • Mario García-Valdez, Leonardo Trujillo, Juan-J Merelo, Francisco Fernández de Vega and Gustavo Olague. The EvoSpace Model for Pool-Based Evolutionary Algorithms, to appear in Journal of Grid Computing (2015).
  • Laurent Vezard, Pierrick Legrand, Marie Chavent, Frédérique Faïta-Aïnseba, Leonardo Trujillo. Detecting mental states of alertness with genetic algorithm variable selection, Applied Soft Computing 32:113-131 (2015).
  • Mauro Castelli, Leonardo Vanneschi and Leonardo Trujillo. Energy Consumption Forecasting using Semantics Based Genetic Programming with Local Search Optimizer, Computational Intelligence and Neuroscience (2015).
  • Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi, Ales Popovic. Prediction of energy performance of residential buildings: a genetic programming approach, Energy and Buildings 102:67-74 (2015).
  • Arturo Sotelo, Enrique D. Guijarro and Leonardo Trujillo. Seizure States Identification in Experimental Epilepsy using Gabor Atom Analysis, Journal of Neuroscience Methods 241:121-131 (2015).
  • R.C. Guitiérrez-Urquidez, G. Valencia-Palomo, O.M. Rodríguez-Elías, L. Trujillo. Systematic selection of tuning parameters for efficient predictive controllers using a multiobjective evolutionary algorithm, Applied Soft Computing 31:326–338 (2015).
  • Victor H. Diaz-Ramirez, Andres Cuevas, Vitaly Kober, Leonardo Trujillo, Abdul Awwal. Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimization, Optics Communications, 338(1): 77-89 (2015).
  • Francisco Fernández de Vega, Leonardo Trujillo, Francisco Chávez, Enrique Mediero and Luis Muñoz. A Hybrid ECJ+BOINC Tool for Distributed Evolutionary Algorithms, Research in Computing Science, Advances in Computing Science, Control and Communications, Mireya Garcia et al. (Eds.), 69, 120-130 (2014).
  • Arturo Sotelo, Enrique Guijarro, Leonardo Trujillo, Luis N. Coria, Yuliana Martínez, Identification of Epilepsy Stages from ECoG using Genetic Programming Classifiers,  Computers in Biology and Medicine 43(11): 1713–1723 (2013).
  • Francisco Fernández de Vega, Gustavo Olague, Leonardo Trujillo, Daniel Lombraña Gonzalez: Customizable execution environments for evolutionary computation using BOINC + virtualization. Natural Computing 12(2): 163- 177 (2013)
  • José Parra, Leonardo Trujillo and Patricia Melin. Hybrid back-propagation training with evolutionary strategies. Soft Computing, pages 1-12, 2013.
  • S. Pinto-Fernández, A. Serrano-Trujillo, V. H. Díaz-Ramírez, L. Trujillo, Reconocimiento facial robusto usando filtros de correlación diseñados a través de optimización combinatoria, Research in Comuting Science, Advances in computing science and control, Vol. 59, pp. 133-144, 2012.
  • Y. Martínez, L. Trujillo, E. Galván López, P. Legrand, A comparison of predictive measures of problema difficulty for classification with Genetic Programming, Research in Comuting Science, Advances in computing science and control, Vol. 59, pp. 159-170, 2012.
  • Gustavo Olague and Leonardo Trujillo. 2012. Interest point detection through multiobjective genetic programming. Appl. Soft Comput. 12, 8 (August 2012), 2566-2582.
  • Leonardo Trujillo, Pierrick Legrand, Gustavo Olague, and Jacques LéVy-VéHel. 2012. Evolving estimators of the pointwise Hölder exponent with Genetic Programming. Inf. Sci. 209 (November 2012), 61-79.
  • L. Trujillo, G. Olague, E. Lutton, F. Fernández de Vega, L. Dozal and E. Clemente, Speciation in Behavioral Space for Evolutionary Robotics. Journal of Intelligent & Robotic Systems 64:34 (December 2011), 323-351 (Springer)
  • Leonardo Trujillo, Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control, Soft Computing, 15:8, 2011, 1551-1567, Springer
  • Gustavo Olague and Leonardo Trujillo, Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming, Image and Vision Computing, 29(7): 484-498, 2011, Elsevier
  • Mónica Beltrán, Patricia Melin, Leonardo Trujillo and Miguel Lopez. Signature recognition with a hybrid approach combining modular neural networks and fuzzy logic for response integration, Journal of Automation, Mobile Robotics and Intelligent Systems, 4(1):20-27, 2010. PIAP.
  • Mónica Beltrán, Patricia Melin and Leonardo Trujillo. Development of modular neural networks with fuzzy logic response integration for signature recognition, Fuzzy Information and Engineering, 1(4): 345-355, 2009. Springer.
  • Leonardo Trujillo, Gustavo Olague. Automated design of image operators that detect interest points, Evolutionary Computation, 16(4):483-507, 2008. MIT Press
  • Oscar Castillo, Leonardo Trujillo, Patricia Melin. Multiple Objective Genetic Algorithms for Path- planning Optimization in Autonomous Mobile Robots, Soft Computing 11(3): 269-279, 2007. Springer.
  • Leonardo Trujillo, Gustavo Olague , Pierrick Legrand , Evelyne Lutton. Regularity based descriptor computer from local image oscillations . Optics Express. 15(10): 6140-6145, 2007.
  • Benjamín Hernández, Gustavo Olague, Riad Hammoud, Leonardo Trujillo, Eva Romero. Visual learning of texture descriptors for facial expression recognition in thermal imagery. Computer Vision and Image Understanding. 106(2-3): 258-269, 2007. Elsevier.
  • Valle, P. A., Coria, L. N., Salazar, Y., Plata, C., & Ramirez, L. A. (2025). Combined Application of CAR-T Cells and Chlorambucil for CLL Treatment: Insights from Nonlinear Dynamical Systems and Model-Based Design for Dose Finding. Hemato, 6(2), 9.
  • Salazar, Y., Valle, P. A., Rodríguez, E., Soto-Cruz, N. O., Páez-Lerma, J. B., & Reyes-Sánchez, F. J. (2023).
  • Mechanistic modelling of biomass growth, glucose consumption and ethanol production by Kluyveromyces marxianus in batch fermentation. Entropy, 25(3), 497.
    Valle, P. A., Coria, L. N., & Plata, C. (2021). Personalized immunotherapy treatment strategies for a dynamical system of chronic myelogenous leukemia. Cancers, 13(9), 2030.
    Valle, P. A., Coria, L. N., & Carballo, K. D. (2021). Chemoimmunotherapy for the treatment of prostate cancer: Insights from mathematical modelling. Applied Mathematical Modelling, 90, 682-702.
    Valle, P. A., Coria, L. N., & Salazar, Y. (2019). Tumor clearance analysis on a cancer chemo-immunotherapy mathematical model. Bulletin of Mathematical Biology, 81(10), 4144-4173.
  • Paz-González, J. A., Gochi-Ponce, Y., Velasco-Santos, C., Alcudia-Zacarias, E., Zizumbo-López, A., Trujillo-Navarrete, B., Morales-Contreras, O. A. and Villarreal-Gómez, L. J., Enhancing Polylactic Acid/Carbon Fiber-Reinforced Biomedical Composites (PLA/CFRCs) with Multi-Walled Carbon Nanotube (MWCNT) Fillers: A Comparative Study on Reinforcing Techniques, Journal of Composites Science, 2025, 9, 167. https://doi.org/10.3390/jcs9040167
  • Jiménez-Vázquez; A., Jaimes-López, R., Morales-Bautista, C. M., Pérez-Rodríguez, S.l., Gochi-Ponce; Y., Estudillo-Wong, L. A., Catalytic Applications of Natural Iron Oxides and Hydroxides: A Review, Catalysts 2025, Volume 15, Issue 3, 236. https://doi.org/10.3390/catal15030236
  • Romero-Orellana, L. A., López-Martínez, J. M., Calva-Yáñez, J. C., Oropeza-Guzmán, M. T., Gochi Ponce, Y., Preparación de nanotubos de carbono dopado con nitrógeno decorado con magnetita por técnica de coprecipitación, Aristas: Investigación Básica y Aplicada. ISSN 2007-9478, 11, 19, 2024, 52-55. https://www.researchgate.net/publication/385418049_Preparacion_de_nanotubos_de_carbono_dopado_con_nitrogeno_decorado_con_magnetita_por_tecnica_de_coprecipitacion
  • Mendoza Villicaña, A. Yadira Gochi Ponce, Daniel Grande, Cornejo Bravo José Manuel, Arturo Zizumbo López, Marlon César González Joaquín, Rocio Alejandra Chávez Santoscoy, Juan Antonio
  • Paz González, Nina Bogdanchikova, Graciela Lizeth Pérez González, and Luis Jesús Villarreal-Gómez, Evaluation of strategies to incorporate silver nanoparticles into electrospun microfibers for the preparation of wound dressings and their antimicrobial activity, Polymer-Plastics Technology and Materials, Taylor & Francis, 62:8, 2023, 1029-1056. https://doi.org/10.1080/25740881.2023.2181703
  • Moreno-Grijalva, G. I., Alonso-Núñez, G., Paraguay-Delgado, F., Oropeza-Guzmán, M. T., Gochi-Ponce, Y., Synthesis of bimetallic PtxWySz nanocrystals as potential cathodic electrocatalysts for Proton Exchange Membrane Fuel Cell, Materials Letters 341, 2023, 134254, 1-4. https://doi.org/10.1016/j.matlet.2023.134254
  • Áreas de interés:Síntesis y Caracterización Fisicoquímica de Materiales Nanoestructurados Basados en Carbono (Nanotubos y Grafeno), Preparación, Síntesis y Caracterización de Materiales Compuestos Multifuncionales Basados en Metales de Transición y Carbono para Celdas de Combustible y Aplicaciones Biomédicas, Estudio y Aplicación de Nanomateriales en Sistemas Para la Generación de Energía Eléctrica y el Área Biomédica.
  • Mauro Castelli , Leonardo Trujillo , Leonardo Vanneschi . Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer. in Computational Intelligence and Neuroscience. 2015:1-8. (2015). Hindawi Publishing Corporation. ISSN 1687-5265.
    http://dx.doi.org/10.1155/2015/971908 Descargar
  • Leonardo Trujillo , Luis Muñoz , Edgar Galván-López , Sara Silva . neat Genetic Programming: Controlling bloat naturally. in Information Sciences. 333:21-43. (2016). Elsevier BV. ISSN 0020-0255.
    http://dx.doi.org/10.1016/j.ins.2015.11.010
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