Matthew Duggan

My previous research background has been to apply abiotic solutions to biotic problems, specifically continuing to bridge the gap between machine learning tools and ecological inferencing. My particular research interest is in utilizing the acoustics of fish to understand habitat resiliency through functional biodiversity of mesophotic coral reef systems.  Through a variety of innovative methodologies and optic-acoustic systems, my team and I plan to form the foundation of a species-specific acoustic library for fish.

While not having a typical acoustic background, I have a strong background in a variety of “big data” in-situ sensor modeling, including animal camera trap object classification, spatio-temporal mapping through unmanned aircraft systems, and biogeochemical sensing prediction optimizations.  I want to take these different perspectives and apply them in the realm of bioacoustics. 

When I am not working and if I can’t spend every second out on or in the water, I’m hiking, flying drones, or google earthing new dive sites. 

Bio Details: Computational ecology in fishery acoustics, machine learning, remote sensing, and combining visual and audio species identification systems in mesophotic reef systems.