Galvanin's research interests lie at the interface between mathematical modelling and experimentation. The research activity is particularly focused on the use of advanced computational tools for the development of predictive models for the characterisation of complex systems in both chemistry and physiology.

Dr. Galvanin has a specific expertise in the following areas:

• Optimal experimental design for model identification
  
• Kinetic modelling, chemical reactor modelling
  
• Pharmacokinetics/pharmacodynamics modeling
  
• Modeling of physiological systems
  
• Machine learning-assisted model identification
  

The current research activity is primarily focused on the optimal design of experiments for i) the identification of kinetic models in microreactor platforms; ii) the development of pharmacokinetic models for the detailed study of physiological systems.