Dr. Efrén Mezura-Montes is a full-time researcher at the Artificial Intelligence Research Center, University of Veracruz, MEXICO. His research interests are the design, analysis and application of bio-inspired algorithms to solve complex optimization problems. He has published over 110 papers in peer-reviewed journals and conferences. He also has one edited book and six book chapters published by international publishing companies. From his work, Google Scholar reports more than 4,600 citations.

Dr. Mezura Montes is member of the IEEE Computational Intelligence Society Evolutionary ComputationTechnical Committee and he is also member of the IEEE Systems Man and Cybernetics Society Soft Computing Technical Committee. He is also the founder of the IEEE Computational Intelligence Society task force on Nature-Inspired Constrained Optimization.  

1. María-Guadalupe Martínez-Peñaloza and Efrén Mezura-Montes, Immune Generalized Differential Evolution for Dynamic Multi-Objective Environments: An empirical study, Knowledge-Based Systems, 2017, DOI: 10.1016/j.knosys.2017.11.037.
2. Saúl Domínguez-Isidro and Efrén Mezura-Montes, A Cost-Benefit Local Search Coordination in Multimeme Differential Evolution for Constrained Numerical Optimization Problems, Swarm and Evolutionary Computation, 2017, DOI;10.1016/j.swevo.2017.10.006 .
3. Héctor Cervantes-Culebro, Carlos A. Cruz-Villar, María-Guadalupe Martínez-Peñaloza, Efrén Mezura-Montes, Constraint-Handling Techniques for the Concurrent Design of a Five-Bar Parallel Robot, IEEE Access, 5(1):23010-23021, 2017, DOI: 10.1109/ACCESS.2017.2764883.
4. Efrén Juárez-Castillo, Nancy Pérez-Castro and Efrén Mezura-Montes, An improved centroid-based boundary constraint-handling method in differential evolution for constrained optimization, International Journal of Pattern Recognition and Artificial Intelligence, 31(11), 2017 DOI: 10.1142/S0218001417590236.
5. María-Yaneli Ameca-Alducin, Efrén Mezura-Montes and Nicandro Cruz-Ramírez, Differential Evolution with Combined Variants and a Repair Method to Solve Dynamic Constrained Optimization Problems. An empirical study, Soft Computing, pages 1-30, DOI:10.1007/s00500-016-2353-1, 2016.

1. Co-Chair of the Special Session on Nature-Inspired Constrained-Optimization at the 2018 IEEE World Congress on Computational Intelligence.
2. Co-Chair of the Special Session on Differential Evolution: Past, Present and Future at the 2018 IEEE World Congress on Computational Intelligence.
3. 2017 IEEE Congress on Evolutionary Computation Tutorial Speaker.
4. Founder of the IEEE Computational Intelligence Society EC Technical Committee Task Force on Nature-Inspired Constrained Optimization.
5. 2013 IEEE Congress on Evolutionary Computation Special Session Chair.