Education
- PhD at University of California – San Diego
Experience
Eric develops and applies machine learning techniques, informed by (mostly marine) ecological questions and engineering constraints, to facilitate observing systems that address long-standing scientific questions with societal relevance. He leads the AI team at the UK National Oceanography Centre (NOC) where his team works on diverse problems, from decision making on autonomous systems to analyzing global-scale model output.
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 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.
Selected Publications
Burns, J.A., K.P. Becker, D. Casagrande, J. Daniels, P.L.D. Roberts, E.C. Orenstein, D.M. Vogt, Z.E. Teoh, A. Yin, B. Genot, D.F. Gruber, K. Katija, R.J. Wood, B.T. Phillips. 2024. An integrated digital holotype strategy for delicate deep-sea organisms. Science Advances. [paper]
E.C. Orenstein and K. Barnard. 2024. FathomNet 2024 Competition – What on Earth is that?! Novel category discovery in the deep sea. 11th Fine-Grained Visual Categorization Workshop at CVPR 2024. [competition][git]
Eric’s Google Scholar Profile
Eric’s NOC profile
