I am a doctoral student in the StatML CDT, supervised by François Caron and Mark van der Wilk. Prior to coming to Oxford, I studied at Bocconi University in Milan.

I am broadly interested in statistical machine learning and Bayesian inference.

I obtained my MSc degree in Mathematics from Karlsruhe Institute of Technology  in 2020 and my PhD from Université libre de Bruxelles in 2023. Since October 2023 I am a Postdoctoral Researcher at the University of Oxford under supervision of Gesine Reinert.

• Stein's method with applications to Statistics
• Goodness-of-Fit
• Directional Data

BMath, University of Waterloo (2019)

MSc, University of Waterloo (2022)

Antibodies work by binding to their targets (antigens), and either inhibiting their function or activating other components of the immune system. Predicting the mode by which an antibody binds to its cognate antigen is called antibody-antigen complex modelling or docking. While general protein complex prediction has seen great improvements in recent years, driven by methods such as AlphaFold Multimer, antibody-antigen complexes are still difficult to model because we rarely have useful homologs to provide co-evolutionary information. My DPhil project is focused on developing new machine learning docking models to more accurately predict antibody-antigen complexes.