David Angwenyi

Background

About David Angwenyi

The area of optimisation has been, for many years, a fertile ground for practically applicable research. Studies on optimisation have spawned data assimilation, machine learning, artificial intelligence, which fields have obtained a wide and broad utility in recent years. Among the areas that have benefited from studies on optimisation are the geosciences, numerical weather prediction, climate studies, weather prediction, navigation, robotics, image processing, guidance of objects to space, surveillance, et cetera. I am interested in developing data assimilation algorithms and studying their convergence rates and efficiency. This entails filtering, prediction and smoothing algorithms—both in time-continuous and discrete settings. I am striving to understand and develop theoretical justifications of these algorithms to supplement the ubiquitous numerical results. Alongside, I study stochastic (partial) differential equations, they being the language in which the laws of nature are written.