Call For Papers

Special Session 1: Evolutionary Computation and Bio-Inspired Optimization

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Evolutionary Computation provides a powerful family of population-based optimization and learning methods inspired by natural evolution and biological processes. This special track aims to bring together researchers and practitioners working on theoretical, methodological, and applied advances in evolutionary and bio-inspired computation.
Topics of interest include, but are not limited to, evolutionary algorithms, genetic algorithms, differential evolution, evolutionary strategies, genetic programming, memetic and hybrid algorithms, swarm and bio-inspired optimization, multi-objective and many-objective optimization, constrained optimization, large-scale and dynamic optimization, surrogate-assisted evolutionary computation, parameter adaptation and self-adaptive methods, evolutionary machine learning, neuroevolution, and evolutionary approaches for artificial intelligence.

Please choose Special Session 1 to submit. Submission Link: https://www.zmeeting.org/submission/ctml2026

 

Special Session 1 Chair:

Prof. Daniel Molina Pérez, Instituto Politécnico Nacional, Mexico
Email: dmolinap@ipn.mx
Research Areas: Computer Science

Daniel Molina-Pérez received the Ph.D. degree in Robotic and Mechatronic Systems from the Centro de Innovación y Desarrollo Tecnológico en Cómputo (CIDETEC), Instituto Politécnico Nacional, Mexico City, in 2024. He is currently a Professor-Researcher with the Escuela Superior de Cómputo (ESCOM), Instituto Politécnico Nacional. He is a member of the Artificial Intelligence and Data Science Network of the Instituto Politécnico Nacional. His research interests include evolutionary computation, multi-objective optimization, mixed-integer nonlinear programming, image enhancement, and hybrid optimization methods for solving complex engineering problems. Dr. Molina-Pérez has authored and co-authored multiple articles in indexed journals, including Swarm and Evolutionary Computation, PeerJ Computer Science, and Mathematical and Computational Applications, and has presented his work at leading international conferences such as the IEEE Congress on Evolutionary Computation (CEC). He received the Best Paper Award at the Mexican International Conference on Artificial Intelligence in 2022 and was recognized with the Outstanding Academic Performance Award at the doctoral level, reflecting his academic excellence and research contributions.

Co-Chair:

Dr. Alam Gabriel Rojas-López, Universidad Autónoma de la Ciudad de México, Mexico
E-mail: alam.rojas@uacm.edu.mx
Research areas: Applied Artificial Intelligence, Robotic

Alam Gabriel Rojas-López received his B.Eng. in Control and Automation in 2015 from the Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Zacatenco, Instituto Politécnico Nacional (IPN), Mexico. From 2015 to 2018, he worked as a Project Engineer in the private sector, focusing on the automation of industrial processes. In 2020 and 2025, he received an M.Sc. in Computing Technology and a Ph.D. in Robotic and Mechatronic Systems Engineering from the Centro de Innovación y Desarrollo Tecnológico en Cómputo (CIDETEC), IPN. He currently serves as a faculty member at the Universidad Autónoma de la Ciudad de México (UACM), where he is involved in teaching and research. He has conducted research at the Dalle Molle Institute for Artificial Intelligence Research (IDSIA USI-SUPSI), Switzerland, and has supervised Master's research in collaboration with Politecnico di Milano, Italy. His research interests focus on artificial intelligence and machine learning strategies for optimal control, with applications to robotic, mechatronic, and engineering systems.