Honours Student Jack Jenkins Applies AI to Assist Advancing Wildlife Conservation
Sequeira Lab was excited to have Honours student Jack Jenkins, who is working on AI foundation models to assist our understanding of animal movement.
We are delighted to highlight the work of Jack Jenkins, who joined the Sequeira Lab as an Honours student in an exciting new interdisciplinary collaboration between the ANU School of Computing and the Research School of Biology.
Jack is currently completing his Honours year in the Bachelor of Advanced Computing, specialising in machine learning. His project is co-supervised by Prof John Taylor from the School of Computing and A/Prof Ana Sequeira from the Sequeira Lab, bringing together expertise in artificial intelligence and movement ecology.
For his Honours thesis, Jack is using artificial intelligence (AI) to better understand how animals move. Drawing on publicly available animal tracking datasets, he is developing deep-learning methods that learn from movement records across species to help predict future animal movements. By identifying common patterns in the way animals navigate their environments, Jack's research has the potential to improve our understanding of animal behaviour and contribute to more effective conservation and management strategies.
This work is a natural follow up from recent research from the SequeiraLab, including the 2026 publication led by Dr Jorge Medina, from IFISC in the Ballearic islands, Spain, on Improving prediction region accuracy in marine animal movement with temporal fusion transformer, completed after Jorge's visit to the lab.
Jack came to machine learning through a love of wildlife. He has completed an internship at Gondwana Game Reserve in South Africa, taught wildlife education at Zoo To You in Cairns, and remains an active advocate for crocodile conservation as a spokesperson with CROC QLD. When he is not working on AI and conservation research, Jack enjoys fly fishing, hiking and photographing Australian wildlife, particularly reptiles.
Completing an Honours project is a significant milestone, and we warmly congratulate Jack on reaching this stage of his academic journey.
We look forward to seeing where his innovative combination of machine learning and wildlife conservation takes him next, and we wish him every success as he completes his thesis.
Stay tuned for future updates on Jack's research and achievements.
