Eric’s work lives at the intersection of biology and computer science, enabling unique studies of rapidly fluctuating marine environments. His expertise in artificial intelligence and machine learning has provided novel perspectives on marine population dynamics, how they are impacted by their environment, and how they in turn influence the rest of the ecosystem. He has studied diverse organisms, from plankton to fish; built and maintained imaging devices; worked with autonomous and remotely operated vehicles; and executed field programs as a diver, small boat operator, and scientist aboard global class vessels. At NOC, Eric works on a range of projects from supporting image-based marine sampling to developing Digital Twins. He spends lots of time thinking about sampling strategies for robots and how to get AI models to recognize populations changes in distribution shifted environments.
Before arriving at NOC, Eric was a Research Engineer at the Monterey Bay Aquarium Research Institute in California where he worked on real-time classification of image data on an AUV, studied marine particles in the deep ocean, co-led the FathomNet project, and was a core team member of Ocean Vision AI. He was previously a postdoctoral scholar at the Sorbonne Université’s Villefranche Oceanographic Laboratory working to extract functional trait data from a global plankton image database. He earned his PhD at the University of California – San Diego for his work on fine-grained image classification of marine plankton.
Please see Eric's Google Scholar Profile for a complete list of publications.
