Eric Orenstein is a Research Engineer working in the Bioinspiration Lab with Kakani Katija. His research lives at the intersection of machine learning, ocean imaging, and marine ecology. Automated detection and classification models often fail in the context of rapidly fluctuating ocean ecosystems and conditions. Eric spends a lot of time thinking about the root causes of that behavior and ways of ameliorating them to speed ecological analysis. Currently, Eric is focused on developing autonomous mission planning routines using image data from the new AyeRIS camera system to study gelatinous microorganisms. He also works on the FathomNet project establishing benchmark test sets and designing metrics to improve database interpretability, facilitate access for non-ocean experts, and ease automated model development.

Eric received his PhD at the Scripps Institution of Oceanography developing automated classification approaches to process in situ plankton image data. After completing his degree, he stayed on at Scripps and continued to leverage techniques from his thesis work to investigate cryptic host-parasite interactions and harmful algal bloom formation. Before arriving at MBARI, Eric worked at the Sorbonne Université in the Laboratoire d’Océanographie de Villefranche on automated techniques for extracting functional trait information from images of ocean organisms.