I am a postdoctoral researcher at the Centre for AI Research at DAMTP. My work focuses on uncertainty-aware machine learning for LHC event generation, developing fast and precise surrogate models for scattering amplitudes that provide accurate predictions with well-calibrated uncertainties. 

I am also interested in bridging particle physics and AI, creating methods to extract more precise information from both theoretical predictions and LHC data, building on my experience with global analyses using SMEFT and EDM measurements. Working with AI, I mainly, but not only, focus on the trustworthiness of AI predictions by improving them through appropriate uncertainty introduction and handling, and on the interpretability of those results.  

Research interests:

• Statistical methods in particle physics
• Surrogate networks
• Uncertainty estimation with AI
• Global analyses for SMEFT analyses