We are a diverse group of researchers whose work centers around extracting knowledge from large volumes of ocean acoustic data, which contain rich information about animals ranging from zooplankton, fish, to marine mammals. Integrating physics-based models and data-driven methods, our current work focuses on mining water column sonar data and spans a broad spectrum from developing computational methods, building open source software and cloud applications, to joint analysis of acoustic observations and ocean environmental variables. A parallel but closely related focus of our research involves using echolocating bats and toothed whales as biological model systemss for adaptive and distributed ocean sensing.
[11/30/2021] New paper “Beluga whale (Delphinapterus leucas) acoustic foraging behavior and applications for long term monitoring” was published in PLOS One!
[10/30/2021] New preprint “Echopype: A Python library for interoperable and scalable processing of water column sonar data for biological information” was posted on arXiv!
[10/28/2021] Emilio and Wu-Jung gave the IOOS DMAC webinar on “Scalable, interoperable processing of water column sonar data for biological applications using the echopype Python package”.
[10/05/2021] Wu-Jung gave the UW Data Science Seminar on “Building a toolbox for studying marine ecology using large ocean sonar datasets”.
[09/21/2021] Wu-Jung and Linda successfully completed this summer’s fieldwork evaluating the use of an ADCP-equipped glider as a boiological monitoring tool. Check out NOAA Exploration’s coverage of this mission!
A Python package that enhances the interoperability and scalability in ocean sonar processing.
Matlab code to reproduce all figures in an in-depth tutorial on echo statistics.