I serve as a Postdoctoral Research Associate at the Ineos Oxford Institute for Antimicrobial Research and Chemistry Research Laboratory within the University of Oxford, collaborating closely with the esteemed groups led by Prof. Christopher Schofield, FRS and Prof. Fernanda Duarte.

I am a computational chemist working at the intersection of computational chemistry, chemical biology and machine learning, with a specific emphasis on driving innovations in overcoming Antimicrobial Resistance (AMR). I develop and employ state-of-the-art computational strategies to identify new active drug molecules targeting AMR and investigating their mechanisms of action. These methodologies include electronic structure methods, classical molecular modelling, hybrid quantum mechanics / molecular mechanics (QM/MM) and machine-learning techniques. Prior to my work at Oxford, I worked as a Postdoctoral Research Associate in Dr. Amanda Jarvis' group at The University of Edinburgh. I specialize in structurally modeling artificial metalloenzymes to enhance their efficiency while also innovating the design of new metalloenzymes. My approach integrates various computational techniques, spanning from molecular docking studies to hybrid QM/MM calculations. Preceding this, I earned my PhD degree in 2021 from The University of Manchester, where I worked with Dr. Richard Henchman and Prof. Samuel de Visser, FRS at Manchester Institute of Biotechnology. My research was focused on the development and implementation of algorithms to determine the reactions kinetics and stability of biomolecules.