Wu-Jung Lee

Senior Oceanographer / Principal Investigator

Applied Physics Lab, University of Washington

Acoustic Informatics

Sound is the best information carrier in the ocean. Working at the intersection of physics, engineering and biology, I develop computational methodologies and interpretation frameworks to extract mid- to high-trophic level biological information from ocean acoustic data across multiple spatial and temporal scales.

My current research focuses on integrating physics-based models and data-driven methods to address two fundamental aspects of acoustic sensing:

  • Sampling – how do we collect better data?
  • Inference – what can we learn from the data?

A parallel but closely related focus of my research involves using echolocating bats and toothed whales as biological models for adaptive and distributed ocean sensing.

I am an active contributor to open-source scientific software (see echopype), and have been the lead and co-lead of OceanHackWeek 2018-2021, a workshop dedicated to data science in oceanography.

My research program is funded by the National Science Foundation, the Office of Naval Research, and the National Oceanic and Atmospheric Administration.


  • Sonar Sensing
  • Animal Echolocation
  • Bioacoustics
  • Marine Ecology
  • Reproducible Research


  • PhD in Oceanographic Engineering, 2013

    MIT-WHOI Joint Program in Oceanography

  • BSc in Electrical Engineering, 2005

    National Taiwan University

  • BSc in Life Sciences, 2005

    National Taiwan University



A Python package that enhances the interoperability and scalability in ocean sonar processing.

Echo Statistics

Matlab code to reproduce all figures in an in-depth tutorial on echo statistics.

List of Publications

Recent & Upcoming Talks

Data-driven decomposition of long-term echosounder time series from ocean observatories

Echopype: Interoperable and scalable processing of ocean sonar data

How much more informative are broadband compared to narrowband echoes for biological interpretation?

Active infotaxis as a model for echolocation

Rising to the challenges of big acoustic data

Recent Posts

First JASA *tweetorial* on echo statistics!

Our echo statistics tutorial materials became the first ever JASA tweetorial today.

ASA/CAA special session: Machine learning and data science in ocean acoustics

Super excited to host the special session Machine Learning and Data Science Approaches in Ocean Acoustics in the upcoming ASA/CAA joint meeting in Victoria, BC!

Watching a solar eclipse using OOI sonar

Data from the OOI cabled echosounders are perfect for watching the effects of a sonar eclipse in the ocean.

Scooping up zooplankton from the ocean

My second time sailing with the UW OOI Cabled Array team, with a mission to scoop up some zooplankton from the ocean.