Florence Vermeire is a postdoctoral associate in Chemical Engineering. She works on kinetic model development and machine learning for chemical property prediction. Her current work focusses on transfer learning and active learning to improve solvation-related property prediction. During her PhD thesis, she worked on the automated development of kinetic models for the combustion of biofuels and the production of green chemical from renewable resources. Florence is originally from Belgium and outside of the lab she is engaged in DEI initiatives and enjoys to go for a swim.
active learning, machine learning, multiscale modeling, theoretical chemistry
Country of Origin
Belgian American Educational Foundation postdoctoral fellowship