Dr. Emmanuel Dufourq serves as a Resident Researcher and Senior Lecturer, specializing in machine learning applications for conservation and environmental monitoring. His research focuses on developing innovative computational approaches to address challenges in biodiversity conservation and ecological monitoring.
Dr. Dufourq leads multiple research projects applying machine learning to bioacoustics and environmental data, including work on monitoring endangered species and developing algorithms for acoustic data analysis in data-scarce environments.
As a supervisor to several postgraduate students, he guides research in areas such as machine learning for bioacoustics, compressed sensing, and conservation technology applications, contributing significantly to both the academic community and practical conservation efforts.