Dr Lorene Jeantet is a postdoctoral fellow at AIMS, where she has been part of the Machine Learning for Ecology research group since 2022. Driven by a deep passion for wildlife and the natural world, her work focuses on harnessing mathematics and deep learning to advance biodiversity conservation. She develops innovative, user-friendly deep learning tools that enhance wildlife monitoring, with the goal of improving our understanding of endangered species and supporting their protection.
Lorene began her research career at the French National Centre for Scientific Research (CNRS), where she completed a PhD in behavioural ecology and conservation biology focused on marine turtles in Martinique and French Guiana. During her doctorate, she entered the world of deep learning by building a model to automatically identify underwater turtle behaviour from bio-logger data, or animal-attached sensors.
Her growing interest in this field led her to join AIMS, where she now applies deep learning across a wide range of ecological monitoring technologies, from acoustic and video recorders to bio-loggers and camera traps. Her work spans species ranging from amphibians to African penguins, with marine turtles remaining at the heart of her research.
Inspired by South Africa’s rich biodiversity, Lorene continues her research at AIMS, where she was appointed as a Junior Researcher in April 2025. This role enables her to contribute further to teaching and student supervision alongside her research, with the goal of empowering the next generation of African scientists to play leading roles in conservation and contribute to the protection of the continent’s unique wildlife.
