Quantitative research and data analysis focused on extracting reliable,
decision-ready insight from complex datasets, using reproducible and
well-documented analytical workflows.
Research Experience
Led independent, multi-year research projects involving large and complex scientific datasets.
Designed and maintained reproducible data-analysis pipelines (Python, MATLAB).
Applied rigorous quality control, validation, benchmarking, and cross-checking procedures.
Produced peer-reviewed publications in leading international scientific journals.
Worked within international, multidisciplinary research teams across institutions and countries.
Translated complex technical analyses into clear, decision-ready outputs for diverse stakeholders.
Process, Methods, and Quality Assurance
Developed new analytical workflows to improve reliability and reduce uncertainty in complex datasets.
Implemented formal validation and cross-validation procedures as part of routine analysis.
Worked to strict documentation, governance, and reproducibility standards.
Version-controlled analytical code and maintained auditable research pipelines.
Project Delivery, Leadership, and Engagement
Planned, organised, and executed international research and fieldwork campaigns.
Field experience across multiple global locations, including Western Australia, Brazil, and Canada.
Managed logistics, scheduling, risk, and data acquisition in remote and operationally challenging environments.
Presented research at international conferences and invited university seminars worldwide.
Invited talks and participation at institutions including Oxford, Cambridge, Plymouth, Southampton, and Leeds.
Regular contributor to AGU (San Francisco).
Planned, budgeted, and convened an international scientific conference with invited speakers.
Delivered outreach and mentoring activities, communicating complex scientific results to non-specialist audiences.
Qualifications
PhD, Geophysics — University of Liverpool
MSc, Geophysics — University of Liverpool
Advanced training in quantitative methods, data analysis, and scientific computing