About

As a Biodiversity Data Scientist, I have worked with a diverse range of collaborators, including universities, environmental organizations, and government agencies, delivering valuable insights and solutions for biodiversity conservation and invasive species risk mapping.

My research leverages machine learning and AI to understand and predict biological invasions and species distributions in response to global change.

I am passionate about open science and promoting FAIR data to further biodiversity conservation. Through my research, I aim to provide transparent, reproducible workflows and insights that can inform policy and advance our predictive understanding of biodiversity dynamics.

My Values

Integrity

The highest standards of honesty, ethics, and transparency are maintained in all data analysis and research practices.

Excellence

Striving for excellence in every project, I leverage my expertise in machine learning, geospatial analysis and cutting-edge approaches to deliver robust research for biodiversity conservation.

Open Science

I adhere to FAIR ( Findable, Accessible, Interoperable, Reusable) data principles to help advance biodiversity conservation and transparent decision-making. My research outputs are shared via open access publications, GitHub and Zenodo.