During his PhD, Michael focused on improving the operational modeling of geomagnetically induced currents. To ensure actionable outputs, he developed robust data driven approaches that included power system and geophysical influences with their associated uncertainties.
As a Schmidt Science Fellow, Michael harnessed computational physics to help us better understand the fundamental underlying phenomena, such as solar storms, and forecast their impact in advance. At Imperial College London, he works with space physics researchers to develop an operational space weather forecasting capability using faster than real-time magnetohydrodynamic simulations of the near-Earth environment and link these to ground effects. Dually affiliated with Imperial-X, he plans to couple interpretable, physics inspired machine learning approaches to generalize this forecasting capability to regions often under-represented in operational modeling.
Michael hopes to deploy a coupled forecasting capability to his home in South Africa, and in the process provide a catalyst for further region-specific research in the field. More generally, he aims to bridge the gap between research and operations, increasing the resilience of modern infrastructure in the face of extreme space weather events.