Paul’s research interests include but are not limited to; renewable energy technologies, pattern recognition, signal processing, time series analysis, forecasting, model estimation, building and evaluation as applied to different problems in different paradigms. In line with his research, he has co-authored and published scientific papers in the energy, pattern recognition, image processing and data science fields and some of his work has been presented at IEEE’s International Renewable Energy Congress and IEEE’s International Conference on Image Processing.

He has also conducted data-driven research in the area of risk assessment particularly for offshore wind farms in the North Sea (a portfolio of over 38 offshore wind farms) and this work is pending publication in the Royal Society Open Science Journal.

Paul holds a Bachelor’s degree in Computer Engineering (First Class Hons.) from Makerere University in Uganda and a Master’s degree in Electrical and Computer Engineering from Carnegie Mellon University, specializing in Data Science and Machine Learning.