Emmanuel De-Graft Johnson Owusu-Ansah

Research ExpertiseMy research interests are Computational Statistics, Uncertainty Quantification, Data Science (Machine Learning and Visualisation), and Bayesian Statistics with emphasis on applications in reliability, risk and hazard assessment, general modeling in engineering, applied sciences, Finance, and regional climate prediction. In particular, I am interested in developing tools to examine the complex nature of these fields to bring insights and solutions. Much of my work in this area involves modeling (reliability, risk, predictive, prescriptive) framework processes, with a Bayesian description of input parameters through quantification of parametric uncertainty and its impact on decision-making processes driven by data.Additionally, I am involved in scientific visualization in engineering and the applicability of Artificial Intelligence technologies toward on-farm agricultural problems and industry optimisation domains. Brief BioI am a Senior Lecturer in Statistics and Actuarial Science at the Kwame Nkrumah University of Science and Technology, Faculty of Physical and Computational Science, College of Science. I received my MPhil. in Applied Mathematics under the National Institute for Mathematical Science (NIMS) Department of Mathematics, KNUST, and Ph.D. in Mathematical Statistics/Risk and Reliability from the mobility program of the University of Copenhagen, Technical University of Denmark, Sokoine University in Tanzania, and Kwame Nkrumah University of Science and Technology. Hold postgraduate certificates from Cranfield University UK, Michigan State University USA, and Maastricht School of Management Netherlands. Currently, at KNUST, I am the program coordinator for Distance Learning and deputy postgraduate programs coordinator for the Department of Statistics and Actuarial Science. TeachingMy teaching specialties revolve around Computational, Probability, Bayesian Statistics, Food Modeling, Engineering Data Analysis, Risk and Reliability Engineering, and other Applied Data Science courses.