I`ve worked closely with Will on the development of advanced AI-driven workflows to improve Species Distribution Models (SDMs), including the design of a scalable environmental data pipeline built on Google Earth Engine to support ecological analyses and actionable biodiversity insights for WildMon. Will played a key role in integrating machine-learning approaches with environmental covariates, helping translate complex data streams into robust, interpretable models that directly inform conservation decision-making.

In parallel, Will led the development of SDMs to predict chimpanzee occurrence, collaborating with Jane Goodall Institute, supporting efforts to better understand and protect critical habitat for this endangered species. Beyond his strong technical skills, Will is exceptionally easy to work with, highly responsible, proactive, and collaborative, with excellent communication skills. He consistently brings clarity, thoughtfulness, and professionalism to interdisciplinary teams, making him a real asset to any conservation or data-science project

Working with Will on Power BI and machine learning was such a positive experience. He created a comfortable learning environment, adapted to my pace, and tailored each lesson to our goals. With Will's guidance, I gained practical skills quickly that I continue to rely on in my current work. By explaining complex topics with clarity, he helped me build confidence I didn’t have before and I’m very grateful for the opportunity to have worked with him.

Will was fantastic to work with on a highly diverse array of projects. He consistently transformed complex data landscapes into highly interpretable dashboards, which were quickly adapted in response to stakeholder feedback. He quickly built reproducible and complex machine learning models to produce general insights about data generated via DNA barcoding and metabarcoding. I highly recommend Will for all data science and machine learning projects.