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.
[07/2024] Wu-Jung gave a talk on our Echostack software suite and Valentina presented a poster on the Echodataflow package at the Scipy 2024 conference.
[06/2024] Aditya attended the BioAcoustic Summer School (SeaBASS) in the University of New Hampshire and met some inspiring lecturers and students! Wu-Jung also gave a lecture on Fundamentals of Ocean Acoustics!
[05/2024] Wu-Jung and Aditya presented two talks in the Ottawa ASA Meeting on evaluating the hake ML model and the impacts of duty-cycle PAM for bats.
[05/2024] Wu-Jung gave a lecture on active acoustic ocean sensing and a best practice in scientific computing tutorial at ASA School 2024 in Ottawa as an instructor and met some wonderful students!
[04/2024] Wu-Jung and Valentina presented two talks at the WGFAST 2024 meeting in France on pipelines and software tools for echosounder data processing on both ship and cloud.
[04/2024] Wu-Jung presented on Echosounder Data Processing Levels (with contributions from Emilio, Brandyn, and Valentina) at the Global Acoustics INteroperable (GAIN) workshop associated with the WGFAST 2024 meeting.
[03/2024] Wu-Jung and Valentina hosted 2 Capstone teams in the Master of Science in Data Science program for sonar data processing and automatic bat call detection.
[12/2023] We welcome Dr. Brandyn Lucca to join Echospace as a SEED postdoctoral fellow!
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.