Climate System Dynamics and Prediction
Atlantic Multidecadal Variability (AMV)
Extreme events statistics and attribution
Digital Technology for Atmospheric Science Strategy
Interests: Climate dynamics, sub-seasonal to decadal prediction, climate modelling, jet streams, extreme events
Summer Research Intern (2025)
Supervisor: Ioana Colfescu
Permanent Organisation: The Centre for Environmental Data Analysis
PhD Candidate (2025-)
Supervisor: Ioana Colfescu
My project focuses on Compound Extremes, when multiple hazards occur together, often leading to enhanced impacts. The aim is to use advanced Machine Learning methods to better understand these compound extremes and their future impacts. This includes characterising them and identifying their physical drivers, but also exploring the relative contribution of internal climate variability and anthropogenic climate change to the occurrence of these events.
PhD Candidate (2025-)
Supervisor: Ioana Colfescu
My project explores cross-scale interactions in the climate system, focusing on the North Atlantic region. I am investigating how processes at small scales (like sub-daily weather events) influence and are influenced by larger-scale seasonal and inter-annual variability. By using advanced machine learning and climate model simulations, I aim to understand how these interactions shape atmospheric circulation patterns, affect predictability, and respond to long-term climate change.
Alumni: