Dr. Fidel Isheanesu Mugunzva | Artificial Intelligence | Research Excellence Award

Dr. Fidel Isheanesu Mugunzva | Artificial Intelligence | Research Excellence Award

Zagatto Research Institute | Zimbabwe

Dr. Fidel I. Mugunzva is a dynamic scholar and research professional with over a decade of corporate experience, bridging industry practice with academic excellence. He holds a PhD in Management Studies from the University of South Africa, with research interests centered on artificial intelligence, AI ethics, entrepreneurship, and digital transformation. Currently serving as a Research Lead at Zagatto Research Institute, he has led impactful data-driven projects and strategic initiatives. Dr. Mugunzva has published in peer-reviewed journals, presented at international conferences, and contributed to higher education as a lecturer and research supervisor, demonstrating strong commitment to interdisciplinary research and innovation.

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Mais Mayassah | Machine Learning Applications | Research Excellence Award

Ms. Mais Mayassah | Machine Learning Applications | Research Excellence Award

Structural and Geotechnical Engineering Department, Szechenyi Istvan University, Gyor, Hungary | Hungary

Ms. Mais Mayassah is a dedicated Water and Geotechnical Engineer and PhD researcher at Széchenyi István University, Hungary, specializing in structural engineering, geotechnics, and hydraulic systems. With extensive academic and professional experience, she has contributed to advanced research within the National Laboratory for Water Science and Water Security, focusing on flood resilience, levee safety, and climate-driven hydrological challenges. Her background includes roles as a civil engineer and consultant in Syria, where she supervised infrastructure, sanitation, and construction projects, alongside years of university teaching in hydraulics and building materials. Her research integrates numerical modeling, artificial intelligence, and geotechnical analysis to develop innovative, data-driven solutions for sustainable and resilient water infrastructure systems.

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