Before joining IBM as a Research Scientist in AI modelling and simulation, Fabian obtained degrees in environmental and chemical engineering and pursued a PhD in computational physics between UCL, the University of Cambridge, and Imperial College London.
During his PhD, Fabian developed and applied simulations techniques to identify and engineer materials for water desalination, hydrogen storage and catalysis. Specifically, he employed supervised learning methods to facilitate and accelerate accurate molecular dynamics simulations on supercomputers. Among other awards, Fabian was awarded the Christopher Wormald Prize for his significant contributions to the field of thermodynamics. Additionally, he received the prestigious Woodruff Thesis Prize from the IOP Thin Films and Surfaces Group.
After his PhD, Fabian participated in a data science fellowship with faculty AI where he worked in close collaboration with IQVIA leveraging explainability approaches to help pharmaceutical companies make intelligent investment decisions on where to run clinical trials to maximise patient access.
Within IBM Research, Fabian's interests lie within the application and development of state-of-the-art AI methods for replacing molecular simulations of materials with surrogate models.