Doctoral Researcher, Sungkyunkwan University, South Korea
🌍 Dr. Sseguya Fred, born on March 24, 1987, is a dedicated Doctoral Researcher at Sungkyunkwan University, Seoul, South Korea, specializing in water and environmental engineering. With a strong academic background and professional expertise, he integrates advanced technologies like machine learning and remote sensing to address pressing global challenges in hydrology, flooding, and drought analysis. Fred’s research contributions reflect his commitment to sustainable resource management and environmental engineering. 🌱📊
Publication Profile
Scopus
Education
🎓 Dr. Sseguya Fred holds a Doctoral Researcher position at Sungkyunkwan University, Seoul, South Korea, in the Department of Civil, Architectural, and Environmental System Engineering. He earned a Master of Science in Water Resources Technology and Management from the University of Birmingham, UK 🌧️, and a Bachelor of Science in Civil and Water Resources Engineering from the University of Dar es Salaam, Tanzania. 🌊📘
Experience
🔧 Fred worked as an Engineer for Uganda’s Ministry of Water and Environment (2013–2019), overseeing water diversion for dam construction, monitoring water quality 🌿, and ensuring environmental compliance. Since 2020, he has been advancing water and environmental engineering research at Sungkyunkwan University, focusing on machine learning, remote sensing, and hydrological systems. 🛰️💻
Research Interests
📡 Dr. Sseguya Fred’s research spans hydrology and water resource management, remote sensing applications, and the integration of machine learning for analyzing floods and droughts. He is also passionate about environmental engineering and the sustainable management of hydraulic systems. 🌍💧
Awards
🏆 Although specific awards are not listed, Dr. Fred’s academic journey and professional achievements demonstrate his dedication to excellence in environmental engineering and hydrology.
Publications
Deep Learning Ensemble for Flood Probability Analysis
Drought Quantification in Africa Using Remote Sensing, Gaussian Kernel, and Machine Learning