Adrián Alarcon | Network | Best Industrial Research Award

Published on by Environmental Scientists

Mr. Adrián Alarcon | Network | Best Industrial Research Award

Mr. Adrián Alarcon | Network | Researcher at CIRCE – Centro Tecnológico | Spain

Mr. Adrián Alarcon is a researcher specializing in smart grids and intelligent control of electrical power systems with a particular emphasis on modern network-oriented challenges associated with voltage regulation, renewable integration, and artificial intelligence applications in power engineering. Mr. Adrián Alarcon holds advanced technical education in electrical and energy systems, including graduate-level training in smart energy, data science, and related computational disciplines, positioning him at the intersection of engineering and data-driven optimization. His formal training includes master’s degrees in Smart Energy with a focus on renewable energy and digitalization and a Magister in Data Science, along with additional coursework in power system analysis, statistics, and industrial maintenance, reflecting a broad technical foundation in both theoretical and applied facets of energy systems and network control. Professionally, Mr Adrián Alarcon is currently employed as an Investigator (Smart Grid Researcher) at CIRCE – Centro Tecnológico in Zaragoza, Spain, where he leads and contributes to research projects aimed at improving voltage control and operational resilience of electrical grids, particularly through integrating artificial intelligence and neuroevolutionary approaches into classical power system control frameworks; his work involves rigorous simulation, algorithm development, and comparative analysis of machine learning and heuristic optimization techniques for autonomous grid regulation and smart network performance. Before his current role, Mr. Adrián Alarcon accumulated extensive industry experience, including technical and leadership positions in system protection, operations analysis, electrical interconnections, and teaching, demonstrating his ability to bridge academic research with real-world power engineering challenges. His research interests revolve around network-centric voltage regulation, autonomous control agents, deep reinforcement learning, and evolutionary computing applied to power systems, with a core focus on enhancing grid stability, efficiency, and adaptivity under variable renewable generation and complex operating conditions. Mr. Adrián Alarcon’s research skills encompass advanced programming (Python, C/C++), simulation environments for power systems, neural network design, comparative algorithm evaluation, and metaheuristic optimization, enabling systematic exploration of intelligent control strategies and performance benchmarking against conventional control schemes. While formal awards and honors for Mr. Adrián Alarcon’s academic work are not broadly publicly documented, his publication in a peer-reviewed journal and leadership in applied research projects reflect professional recognition within the smart grid research community. In conclusion, Mr Adrián Alarcon stands out as a dedicated engineer-scientist focused on addressing key network challenges in modern electrical systems, with a demonstrable trajectory of integrating data-driven intelligence into the evolution of smart grid technologies.

Academic Profile: ORCID

Featured Publications:

Alarcón Becerra, A., Albernaz Lacerda, V., Rocca, R., Talayero Navales, A. P., & Llombart Estopiñán, A. (2025). Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems. Inventions, 10(6), 110. Published 2025. Citations: citation data not yet available / indexing pending.

 

 

Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award

Published on by Environmental Scientists

Dr. Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award

International Society For Executive Learning | Portugal

Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures.

Profiles: Scopus | Orcid | Google Scholar | Researchgate

Featured Publications

Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240.

Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692.

Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65).

Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116.

Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.