Date(s) - 10/05/2021
4:30 pm - 5:20 pm

Please use this zoom link for the event.

Please join us for a UW Data Science Seminar event on Tuesday, October 5th from 4:30 to 5:30 p.m. The seminar will feature Wu-Jung Lee, Senior Oceanographer at the Applied Physics Laboratory at UW.

“Building a toolbox for studying marine ecology using large ocean sonar datasets”


Abstract: Echosounders are high-frequency sonar systems specialized for monitoring fish and zooplankton. They are the workhorse in observing life in the ocean and are widely used in fisheries and marine ecological studies. The recent explosion of the availability of echosounder data from diverse ocean observing platforms has created unprecedented opportunities to study marine ecosystems at broad spatial and temporal scales. However, this acoustic data deluge has also brought a multitude of challenges, from data access and analysis to interpretation.In this talk I will discuss our work in developing data-driven methodologies and software tools to tackle these challenges. I will show how matrix decomposition techniques can extract biologically meaningful patterns from complex echosounder observations, producing a compact representation that is further conducive to systematic analysis with other ocean variables. This work is accompanied by our development of echopype, an open-source software package to enable interoperable and scalable echosounder data processing. These advances form the foundation for our continuing effort to gain ecological insights from large volumes of echosounder data.

Biography: I am interested in the use of sound – by both human and animals – to observe and understand the environment. My research spans two primary areas: acoustical oceanography, where I develop and apply active acoustic sensing techniques to infer properties of the ocean interior; and animal echolocation, where I combine experimental and computational approaches to understand the closed-loop sensorimotor feedback in echolocating bats and dolphins. In both areas, I focus on fundamental aspects for achieving high confidence active acoustic sensing: 1) sampling – what can we do to collect better information? and 2) inference – how do we make reliable interpretation of echo information? Under these overarching themes, I am working to expand acoustic sensing capability for marine ecosystem monitoring at large temporal and spatial scales, and use echolocating animals as biological models to inspire adaptive sampling strategies in an active acoustic context.

The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.

The 2021-2022 seminars will be hybrid virtual and in-person events, and are free and open to the public.