Dr Lorène Jeantet is a researcher in Machine Learning for Ecology at the African Institute for Mathematical Sciences (AIMS) South Africa, where she specializes in applying deep learning and signal processing to wildlife monitoring. Her work focuses on extracting ecological information from animal-borne sensors, including accelerometers, acoustic recorders, video data, and camera traps, to better understand animal behaviour and support conservation efforts.
She holds a PhD in Behavioural Ecology from the University of Strasbourg (CNRS, France), during which she developed novel deep-learning approaches to automatically identify sea turtle behaviours from bio-logger data. She has been a postdoctoral researcher at AIMS for four years and is currently the leader of the Machine Learning for Ecology research group.
Dr Jeantet has led and contributed to numerous international research projects and has published extensively in leading journals such as Journal of Experimental Biology, Ecological Informatics, Movement Ecology, and Biological Conservation. Her work has been recognised with several awards, including the L’Oréal–UNESCO For Women in Science Young Talent Award in 2020.
Her research and teaching interests include deep learning for ecology, bioacoustics, animal behaviour inference, and the development of transferable AI tools for conservation. She is actively involved in graduate supervision, capacity building in Africa, and scientific outreach, and currently co-leads initiatives to strengthen AI training for ecologists across the continent.
