Abraham Marquez | Power Electronics | Best Researcher Award

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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.

Ameni Chetouane | Computer Science | Best Researcher Award

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Dr. Ameni Chetouane | Computer Science | Best Researcher Award

Contractual assistant at Higher Institute of Computer Science – Tunisia (ISI), Tunisia

Ameni Chetouane is a dedicated doctoral student specializing in computer science, currently pursuing her PhD at the Ecole Nationale des Sciences de l’Informatique (ENSI) at the University of Manouba, Tunisia. Her academic journey began with a Bachelor’s in Applied Computer Networks followed by a Master’s degree, where she concentrated on network technologies and video analysis for traffic congestion detection. She is deeply involved in research aimed at securing Software Defined Networking (SDN) systems against cyber-attacks using Artificial Intelligence (AI) methods.

Profile

Orcid

Education

Ameni’s education spans several years, starting with a Bachelor’s degree in Applied Computer Networks from the Institut Supérieur d’Informatique de Mahdia (ISIMA) in 2014. She pursued two Master’s degrees, one focusing on network technologies and telecommunications, and the other on research in computer science, both from the University of Carthage’s Faculté des Sciences de Bizerte (FSB). Her doctoral studies, commenced in 2021, are focused on the application of AI for intrusion detection systems (IDS) in SDN environments, with a goal to combat cyber-attacks.

Experience

Ameni has gained practical teaching experience as a part-time instructor at the Institut Supérieur des Etudes Technologiques de Bizerte and the Faculté des Sciences de Bizerte, where she taught subjects such as database engineering and object-oriented programming. Her internships, including research at LaBRI, University of Bordeaux, and her professional project at Millénia Engineering, have allowed her to apply theoretical knowledge in real-world network and software development projects.

Research Interests

Ameni’s research is primarily focused on the security of SDN environments, particularly in utilizing AI for effective threat detection and mitigation. Her doctoral thesis specifically explores AI-driven solutions for securing SDN systems against Distributed Denial of Service (DDoS) attacks. She aims to improve the performance of IDSs by incorporating machine learning (ML) and continual learning methods into SDN security architectures, ensuring adaptive and real-time defenses against evolving threats.

Awards

Ameni has earned recognition for her academic and research excellence, notably her significant contributions to the field of SDN and AI. Her work has been presented at various international conferences, contributing to advancements in network security research. While specific awards are not listed, her impact within the academic community, through her publications and conference participations, is considerable.

Publications

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “A comparative study of vehicle detection methods in a video sequence.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2019.

Ameni Chetouane, Sabra Mabrouk, Imen Jemili, and Mohamed Mosbah. “Vision-based vehicle detection for road traffic congestion classification.” Concurrency and Computation: Practice and Experience, 2022.

Ameni Chetouane, Sabra Mabrouk, and Mohamed Mosbah. “Traffic congestion detection: Solutions, open issues, and challenges.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2020.

Ameni Chetouane and Kamel Karoui. “A survey of machine learning methods for DDoS threats detection against SDN.” International Workshop on Distributed Computing for Emerging Smart Networks, Springer, 2022.

Ameni Chetouane, Kamel Karoui, and Ghayth Nemri. “An intelligent ML-based IDS framework for DDoS detection in the SDN environment.” International Conference on Advances in Mobile Computing and Multimedia Intelligence, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “DDoS detection approach based on continual learning in the SDN environment.” International Conference on Hybrid Intelligent Systems, Springer, 2022.

Ameni Chetouane and Kamel Karoui. “Risk-based intrusion detection system in Software Defined Networking.” Concurrency and Computation: Practice and Experience, 2023.

Conclusion

Ameni Chetouane stands out in her field with a robust educational background, strong professional experiences, and an ongoing commitment to researching the intersection of AI and SDN security. Through her published works, she has made significant contributions to securing networks using intelligent methods, focusing on solving complex cyber threats in modern network infrastructures. As she continues her research, her work promises to shape the future of AI-driven cybersecurity in SDN environments.