Alumni (PhD Researcher)
Fernando Vega-Ramon

About
From my undergraduate studies through to my PhD, I was fortunate to contribute to research within this group. My main focus was on combining fundamental science with computational tools to accelerate chemical and biochemical process development. In particular, I brought together first-principles modelling, hybrid modelling and transfer learning techniques to improve our understanding of reaction kinetics and reduce the experimental effort required to develop reliable predictive models for process control, scale-up and optimisation.
I now work as a Process Simulation Engineer at Rivan Industries, where I am supporting the development of modular processes for sustainable synthetic fuel production.
Recent publications
Advancing Catalytic Reaction Rate Model Development with Physics-Guided Hybrid Modeling
Extracting microkinetic insights from macroscopic measurements: A power law modelling framework for catalytic reaction mechanism analysis
Developing a Hybrid Modeling Framework for Enhanced Prediction in Chemical Reaction Kinetics