Jack Hollister

PhD Candidate (2021-)

Project Title: Applying computer vision to natural history collections for ecological, taxonomic, and conservation research

Co-supervision: Dr Phillip Fenberg (University of Southampton)

Funding: INSPIRE DTP (UKRI)

Research Focus: Jack’s PhD research is at the forefront of applying artificial intelligence and computer vision techniques to unlock the scientific potential of natural history collections. His work focuses on developing automated methods for species identification, morphological analysis, and data extraction from digitised museum specimens, with applications spanning ecology, taxonomy, and conservation biology.

Key Research Areas:

• Computer vision and machine learning applications
• Natural history collection digitisation
• Automated species identification
• Morphological analysis and measurement
• Conservation applications of museum data
• Climate change research using historical specimens

Research Significance: Jack’s research addresses a critical bottleneck in biological research - the vast amount of information stored in natural history collections that remains inaccessible due to the time-intensive nature of traditional specimen analysis. By developing automated approaches, his work has the potential to dramatically accelerate the pace of biodiversity research and enhance our understanding of ecological and evolutionary processes.