Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award Published on 14/11/202514/11/2025 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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Prof. MUHAMMAD FAIZAN TAHIR | Engineering | Best Researcher Award Published on 22/05/202422/05/2024 by Environmental Scientists Prof. MUHAMMAD FAIZAN TAHIR | Engineering | Best Researcher Award Post-Doctoral Associate, New York University, United Arab Emirates Prof. Muhammad Faizan Tahir, an esteemed Post-Doctoral Associate at New York University, United Arab Emirates, has been honored with the Best Researcher Award in Engineering. 🏆 His groundbreaking contributions to the field are marked by innovative solutions and rigorous academic inquiry. With a keen focus on advancing knowledge and addressing pressing challenges, Prof. Tahir’s work exemplifies excellence in research. His dedication to pushing the boundaries of engineering science inspires peers and students alike. This accolade serves as a testament to his unwavering commitment to scholarly excellence and his significant impact on the academic community. 🎓 PROFILE Google Scholar , Scopus EDUCATION Prof. Muhammad Faizan Tahir’s academic journey is marked by stellar achievements. He earned his Ph.D. in Electrical Engineering from South China University of Technology, China, showcasing his commitment to scholarly pursuits. 🎓 Prior to this, he completed his MS in Electrical Engineering at The University of Lahore, Pakistan, where he honed his expertise. 📚 His educational foundation was laid at the University of Engineering and Technology, Taxila, Pakistan, where he obtained his BS in Electrical Engineering. 🏫 Prof. Tahir’s diverse educational background equips him with a comprehensive understanding of the field, enabling him to make significant contributions to research and academia. STRENGTHS Prof. Muhammad Faizan Tahir possesses a diverse skill set that encompasses both professional and technical domains. As a skilled communicator, he excels in public speaking and cross-cultural communication, fostering effective collaborations. 🗣️ Proficient in team and administration management, he serves as a motivator and leader, driving projects towards success. 💼 On the technical front, his expertise spans various areas including ensemble artificial neural networks and fully informed particle swarm optimization, enhancing problem-solving capabilities. 🧠 Prof. Tahir is adept in utilizing tools and technologies such as EnergyPLAN, HOMER, MATLAB, and MS Office, facilitating efficient project management and analysis. 🛠️ EXPERIENCE Prof. Muhammad Faizan Tahir’s illustrious career spans prestigious institutions across the globe. As a Post-Doctoral Associate at New York University Abu Dhabi, he pioneers research in sustainable energy technology, focusing on solar PV power forecasting and soiling effects on PV performance. 🌞 Previously, at South China University of Technology, he conducted groundbreaking research on integrated energy systems, showcasing his expertise in exergy analysis and renewable energy integration. 🌐 His journey also includes roles as a Research Scholar and Lecturer at the same institution and as a Lecturer and Lab Engineer at The University of Lahore, Pakistan, where he imparted knowledge in electrical engineering and conducted various labs. 🎓 PROJECTS Prof. Muhammad Faizan Tahir’s academic and research endeavors epitomize innovation and excellence. Currently serving as a Post-Doctoral Associate at New York University Abu Dhabi, UAE, he delves into solar PV power forecasting using machine learning and evaluates soiling effects on PV panel performance, contributing to sustainable energy solutions. ☀️ His prior role at South China University of Technology involved pioneering energy and exergy analysis of China’s integrated energy system, emphasizing renewable energy sources. 🌐 Prof. Tahir’s Ph.D. and MS theses focused on integrated energy system modeling and optimal load shedding, respectively, showcasing his expertise in renewable energy and AI. 🎓 His undergraduate project on intelligent dam monitoring further underscores his multidisciplinary approach to engineering challenges. 🌟 ACHIEVEMENTS Prof. Muhammad Faizan Tahir’s accolades and achievements reflect his commitment to excellence and continuous learning. He completed CITI courses and cybersecurity training, enhancing his expertise in research ethics and cybersecurity. 🛡️ His academic prowess earned him the Academic Excellence Award during his Ph.D. studies at SCUT, where he also received the prestigious CSC Scholarship. 🎓 Prof. Tahir’s outstanding academic performance was evident as he secured the 1st rank in MSEE with a remarkable CGPA. 🏅 Additionally, he demonstrated linguistic proficiency by passing the HSK-4 exam and shared his knowledge by delivering lectures on research methodology at SCUT. 📚 These accomplishments underscore his dedication to scholarly pursuits and knowledge dissemination. 🌟 PUBLICATIONS Top Notes Title: Short term electricity load forecasting using hybrid prophet-LSTM model optimized by BPNN Year: 2022 Citations: 122 Title: Integrated energy system modeling of China for 2020 by incorporating demand response, heat pump and thermal storage Year: 2019 Citations: 91 Title: A Novel Algorithm for MPPT of an Isolated PV System Using Push Pull Converter with Fuzzy Logic Controller Year: 2020 Citations: 68 Title: Optimizing size of variable renewable energy sources by incorporating energy storage and demand response Year: 2019 Citations: 64 Title: A comprehensive review of 4E analysis of thermal power plants, intermittent renewable energy and integrated energy systems Year: 2021 Citations: 59