About
Luca Riezzo is a PhD researcher in the “Intelligent Chemical Systems Engineering Research Group”. After graduating with an MEng in Chemical Engineering in 2025, he began doctoral research focused on applying machine learning within chemical engineering to improve process understanding, modelling, and optimisation. His PhD project, “An AI-Enabled Self-Driven Laboratory Framework for Catalytic Reaction Kinetics Discovery,” combines physics-guided symbolic regression with model-based design of experiments to accelerate the development of interpretable kinetic models for catalytic reaction systems. His research aims to reduce experimental burden, improve model transparency, and support the development of self-driving laboratories, digital twins, and more efficient chemical manufacturing.
Recent publications
A Data-Efficient Symbolic Regression Framework for Automated Interpretable Bioprocess Modelling
Accelerating bioprocess digital twin development by integrating hybrid modelling with transfer learning