Ing. David Laud Amenyo Fiase is a Ghanaian engineer, academic, and researcher with over 17 years of experience spanning electrical engineering, higher education, artificial intelligence, financial engineering, and cybersecurity. He serves as a Lecturer and Acting Head of the Engineering Department at Regent University College of Science and Technology in Accra, Ghana. He holds a Bachelor of Engineering in Electrical Engineering and a Master of Science in Electrical Systems and Networks from Moscow Power Engineering Institute, Russia, as well as a Master of Science in Financial Engineering from WorldQuant University, USA. He is currently pursuing doctoral studies at Girne American University, Cyprus, in collaboration with Regent University College of Science and Technology. His professional expertise encompasses electrical power systems, engineering education, artificial intelligence, machine learning, network security, and financial technology, combining technical research with academic leadership and interdisciplinary engineering applications.Fiase’s research interests focus on the integration of Artificial Intelligence and Machine Learning, Electrical Power Systems, Cybersecurity, Quantum Computing, Financial Engineering, and FinTech. His research explores deep learning architectures, including convolutional and recurrent neural networks, transformer models, and their applications in industrial systems, flight simulation, and banking. His electrical engineering interests include power system stability, fault classification, and deep learning-based analysis of transmission lines, while his cybersecurity research addresses intrusion detection, quantum computing techniques, and the ethical implications of offensive cybersecurity. He also investigates AI-driven financial sustainability for small and medium-sized enterprises and the implications of evolving technological standards for institutions such as the Electricity Company of Ghana. His combination of engineering practice, academic leadership, and interdisciplinary research makes him well suited for academic research and peer review in Electrical Engineering, Power Systems, Artificial Intelligence, Machine Learning, Cybersecurity, Network Security, Quantum Computing, Financial Engineering, Financial Technology, and Engineering Education.