
Analytical and data-driven Master’s student specialising in computational modelling, advanced statistics, and machine learning. Proficient in Python and R, with proven experience developing custom computer vision pipelines and implementing complex multivariate frameworks like Compositional Data Analysis. Adept at integrating large-scale, heterogeneous datasets to uncover underlying biological patterns.
AI-Driven Morphological Analysis of Historical Landscape Paintings | 01/2026 - Current | Imperial College London.
Developed a custom computer vision pipeline using fine-tuned transformer and CNN models to automate the classification of vegetation morphotypes in a dataset of 300+ historical paintings, integrating Shannon Diversity metrics and Compositional Data Analysis (ILR) to quantify ecological trends in art history.
Hydraulic strategies and stress responses in Q. robur, F. sylvatica, and F. excelsior under climatic and pathogenic pressure | 01/2025 - 06/2025 | University of Greenwich.
Conducted ecological research analysing hydraulic responses of Quercus robur, Fagus sylvatica, and Fraxinus excelsior under drought and pathogen stress using field sensors (sap flow, dendrometers) and R-based modelling; generated insights for forest resilience and rewilding strategies.
University of Greenwich, Sustainability Volunteer, London | 2023-09, 2024-06
Collaborated with a team of students and staff to promote urban agriculture and sustainable food sources on campus.
Dr. Will Pearse Associate Professor in Evolutionary Ecology
Department of Life Sciences (Silwood Park)
Email: will.pearse@imperial.ac.uk
Phone: +44 20 7594 2322
Relationship: Primary research supervisor
Dr.Samraat Pawar Professor of Theoretical Ecology
Department of Life Sciences (Silwood Park)
Email: s.pawar@imperial.ac.uk
Phone: +44 20 7594 2213
Relationship: Academic tutor