Abraham Marquez | Power Electronics | Best Researcher Award

Dr. Abraham Marquez | Power Electronics | Best Researcher Award

Researcher at Universidad de Sevilla | Spain

Dr. Abraham Márquez Alcaide is a distinguished researcher in electronic engineering, renowned for his pioneering contributions to power electronics, advanced modulation strategies, and predictive control systems. Currently based at the University of Seville, he has played a vital role in the TIC-109 research group, advancing modular power converter technologies with a focus on improving system reliability, efficiency, and lifetime through smart thermal and predictive maintenance control. His prolific academic output includes over ninety peer-reviewed publications in leading high-impact journals and international conferences, several of which are recognized as highly cited by the Web of Science. Dr. Márquez has collaborated globally with eminent scholars and research institutions, including the Harbin Institute of Technology in China and Universidad Técnica Federico Santa María in Chile, fostering innovation in renewable energy integration, electric vehicle charging systems, and industrial automation. A multiple recipient of the IEEE Industrial Electronics Best Paper Award, he is widely respected for his ability to bridge theoretical advancements and industrial applications. Beyond research, he is actively engaged in academic leadership, mentoring numerous postgraduate students, organizing international conference sessions, and contributing to editorial and peer-review processes in reputed journals. His expertise spans modulation techniques, model predictive control, and active thermal management in high-reliability power electronic systems. With his visionary approach and international recognition, Dr. Márquez stands out as a leading figure shaping the future of smart, efficient, and sustainable power conversion technologies.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

Vazquez, S., Leon, J. I., Franquelo, L. G., Rodriguez, J., Young, H. A., & Marquez, A., et al. (2014). Model predictive control: A review of its applications in power electronics.

Liu, J., Vazquez, S., Wu, L., Marquez, A., Gao, H., & Franquelo, L. G. (2016). Extended state observer-based sliding-mode control for three-phase power converters.

Vazquez, S., Marquez, A., Aguilera, R., Quevedo, D., Leon, J. I., & Franquelo, L. G. (2014). Predictive optimal switching sequence direct power control for grid-connected power converters.

Liu, J., Shen, X., Alcaide, A. M., Yin, Y., Leon, J. I., Vazquez, S., Wu, L., et al. (2021). Sliding mode control of grid-connected neutral-point-clamped converters via high-gain observer.

Zhang, J., Tian, J., Alcaide, A. M., Leon, J. I., Vazquez, S., Franquelo, L. G., Luo, H., et al. (2023). Lifetime extension approach based on the Levenberg–Marquardt neural network and power routing of DC–DC converters.

Hugo Terashima Marín | Computer Science | Best Researcher Award

Prof. Hugo Terashima Marín | Computer Science | Best Researcher Award

Professor at Tecnológico de Monterrey | Mexico

Dr. Hugo Terashima-Marín is a distinguished Professor of Computer Science and Intelligent Systems at Tecnológico de Monterrey, Mexico, widely recognized for his pioneering work in computational intelligence and heuristic optimization. His academic foundation spans prestigious institutions in Mexico, the United States, and the United Kingdom, reflecting a strong interdisciplinary background in informatics, artificial intelligence, and knowledge-based systems. As a leading researcher in evolutionary computation, constraint satisfaction problems, and hyper-heuristics, Dr. Terashima-Marín has developed innovative methodologies that bridge artificial intelligence and practical problem-solving across domains such as logistics, medicine, and smart cities. His extensive publication record in high-impact journals demonstrates his global influence in advancing algorithmic design, machine learning integration, and automated reasoning systems. Beyond research, he has mentored numerous doctoral and master’s students, fostering new generations of scientists in computational intelligence. His leadership roles at Tecnológico de Monterrey—directing graduate and doctoral programs and leading research groups in intelligent systems—underscore his commitment to academic excellence and institutional innovation. Recognized by the Mexican National System of Researchers and honored by the Mexican Academy of Sciences and the IEEE, Dr. Terashima-Marín’s contributions have elevated the standards of AI research in Latin America. His current projects explore multi-objective optimization, digital twins for smart city applications, and AI-driven decision support systems, continuing to push the boundaries of how computation can model, predict, and enhance complex human and industrial processes. Through decades of scholarship and collaboration, he remains an influential figure shaping the global discourse on intelligent systems and applied artificial intelligence.

Profiles: Scopus | ORCID

Featured Publications

Ali, F., Ahmed, A., Alipour, M. A., & Terashima-Marin, H. (2025, October 25). Adoption of AI-coding assistants in programming education: Exploring trust and learning motivation through an extended technology acceptance model.

Morales-Paredes, A., Juárez, J., Falcón-Cardona, J., Terashima-Marin, H., & Coello Coello, C. (2025, July 14). Automatic design of specialized variation operators for the multi-objective quadratic assignment problem.

Morales-Paredes, A. I., Falcón-Cardona, J. G., Juárez, J., Terashima-Marín, H., & Coello Coello, C. A. (2025, July 14). Reference point specification in greedy inclusion hypervolume-based subset selection: A study on two objectives. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2025).

Pirzado, F. A., Ahmed, A., Hussain, S., Ibarra-Vázquez, G., & Terashima-Marin, H. (2025, March 11). Assessing computational thinking in engineering and computer science students: A multi-method approach.

Garza-Santisteban, F., Cruz-Duarte, J. M., Amaya, I., Ortiz-Bayliss, J. C., Conant-Pablos, S. E., & Terashima-Marín, H. (2025, February). Selection hyper-heuristics and job shop scheduling problems: How does instance size influence performance