index.json

[{"authors":["leewj"],"categories":null,"content":"Sound is the best information carrier in the ocean. I work at the intersection of physics, engineering, and biology to develop computational methods, models, and interpretation frameworks to extract biological information from ocean acoustic data.\nMy current research focuses on integrating physics-based models and data-driven methods to address two fundamental aspects of acoustic sensing:\n 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 ocean sensing.\nI am an active contributor to open-source scientific software (see Echostack) and am passionate about education. I founded and continue to co-lead OceanHackWeek, a workshop dedicated to data science in oceanography, since 2018, and served on the National Academies committee on Ocean Acoustics Education and Expertise in 2023-2024.\nI lead the Echospace group and our research projects are funded by the National Science Foundation, the Office of Naval Research, and the National Oceanic and Atmospheric Administration.\n","date":1740816e3,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1740816e3,"objectID":"28346b05fea76e7443a9b60d1bcd0a43","permalink":"https://uw-echospace.github.io/author/wu-jung-lee/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/wu-jung-lee/","section":"authors","summary":"Sound is the best information carrier in the ocean. I work at the intersection of physics, engineering, and biology to develop computational methods, models, and interpretation frameworks to extract biological information from ocean acoustic data.","tags":null,"title":"Wu-Jung Lee","type":"authors"},{"authors":["ldr426"],"categories":null,"content":"I have strong eagerness to explore new domains and my ability to grasp complex concepts has allowed me to become a well-rounded and versatile computer science enthusiast.\nMy primary responsibilities within the group is to build echohshader project. Echoshader, an open source project, aims to enhance the ability to interactively visualize large amounts of cloud-based data to accelerate the data exploration and discovery process. Echoshader will be developed in parallel with the ongoing development of echopype, which handles the standardization, preprocessing and organization of echo data.\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"b2205c49ebcfad35ed0ef2eb23a09a5f","permalink":"https://uw-echospace.github.io/author/dingrui-lei/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/dingrui-lei/","section":"authors","summary":"I have strong eagerness to explore new domains and my ability to grasp complex concepts has allowed me to become a well-rounded and versatile computer science enthusiast.\nMy primary responsibilities within the group is to build echohshader project.","tags":null,"title":"Dingrui Lei","type":"authors"},{"authors":["landungs"],"categories":null,"content":"Research Software Engineering I am a research software engineer with a strong focus in designing and maintaining geospatial data analysis systems and software to support environmental research. I am currently providing software solutions for research projects as part of the Scientific Software Engineering Center (SSEC) at UW eScience Institute. I am also a part of the Open-Source Ocean Acoustics Github Organization, developing echopype software for ocean sonar data.\nI have expertise in Python programming, web development, geospatial data analytics, data management solutions, data visualization, relational databases, and system administration. I love to contribute to open-source software and share my knowledge.\nI am a UW School of Oceanography alumnus. I gained my bachelor\u0026rsquo;s degree here with a focus on geospatial data analysis and management through the development of wave sensor buoys to study the spatial variability of oceanic waves. I was also actively involved with Marine Technology Society (MTS), OceanGate Foundation (OGF), Benthic Acoustic Mapping and Survey (BEAMS), Ocean Observatory Initiative-Interactive Oceans (OOI-IO), and served as the Information Technology Lead for Exploration and Remote Instrumentation by Students (ERIS).\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"0bb238bf03ef6262ec0920e5e15e309e","permalink":"https://uw-echospace.github.io/author/don-setiawan/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/don-setiawan/","section":"authors","summary":"Research Software Engineering I am a research software engineer with a strong focus in designing and maintaining geospatial data analysis systems and software to support environmental research. I am currently providing software solutions for research projects as part of the Scientific Software Engineering Center (SSEC) at UW eScience Institute.","tags":null,"title":"Don Setiawan","type":"authors"},{"authors":["emiliom"],"categories":null,"content":"I am an environmental informatics expert with a science background in aquatic biogeochemistry, hydrology and oceanography, focused on the development and implementation of systems for the management and open dissemination of environmental data in marine and terrestrial applications. I have more than 20 years of experience designing, managing and automating data systems and workflows for environmental applications. My work emphasizes collaborative approaches and tools that engage diverse partners, and its scope ranges from local (Pacific NW) to national and global applications.\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"c120d4e9d05d9c1095fbb8f3fd671384","permalink":"https://uw-echospace.github.io/author/emilio-mayorga/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/emilio-mayorga/","section":"authors","summary":"I am an environmental informatics expert with a science background in aquatic biogeochemistry, hydrology and oceanography, focused on the development and implementation of systems for the management and open dissemination of environmental data in marine and terrestrial applications.","tags":null,"title":"Emilio Mayorga","type":"authors"},{"authors":["sbutala"],"categories":null,"content":"I will be working on the echoflow project over the summer. Echoflow, an open source project, aims to orchestrate the echopype data processing functions to ease the ability to process cloud-based/local data through a sequence of functions. Echoflow will be developed in parallel with the ongoing development of echopype, which handles the standardization, preprocessing and organization of echo data.\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"cd3e76e9e4e9a42472392f4985bde51d","permalink":"https://uw-echospace.github.io/author/soham-kishor-butala/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/soham-kishor-butala/","section":"authors","summary":"I will be working on the echoflow project over the summer. Echoflow, an open source project, aims to orchestrate the echopype data processing functions to ease the ability to process cloud-based/local data through a sequence of functions.","tags":null,"title":"Soham Kishor Butala","type":"authors"},{"authors":["zhmiao"],"categories":null,"content":"I work on problems in wildlife conservation and environmental science using big data with high structural complexity (e.g., wildlife imagery data, accelerometer data, and audio data) and state-of-the-art artificial intelligence methods (e.g., computer vision and deep learning). The goal is to address large-scale environmental issues that are not achievable with conventional ecological methods and monitor species responses to climate changes. My research also serves as a bridge between applied computer / data science and ecological / environmental research.\nMy primary responsibilities within the group include:\n The development of algorithms for automatic fish recognition through echosounder imagery  ","date":1712844e3,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1712844e3,"objectID":"6c6c6e27d56bb6566a39f0ccfd31aa5b","permalink":"https://uw-echospace.github.io/author/zhongqi-miao/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/zhongqi-miao/","section":"authors","summary":"I work on problems in wildlife conservation and environmental science using big data with high structural complexity (e.g., wildlife imagery data, accelerometer data, and audio data) and state-of-the-art artificial intelligence methods (e.","tags":null,"title":"Zhongqi Miao","type":"authors"},{"authors":["bcreyes"],"categories":null,"content":"I truly believe that mathematics is a universal language that can solve some of the world’s most difficult problems! I also recognize that to accomplish these tasks, it is absolutely necessary to employ mathematical techniques in conjunction with software development and distributed computing. I am lucky enough to use these skills to support the UW Echospace’s group goal of extracting knowledge from large volumes of ocean acoustic data.\nMy primary responsibilities within the group include:\n The development of echopype Optimizing computational operations for distributed computing Building a scalable cloud cyberinfrastructure  ","date":1651075800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1651075800,"objectID":"81f9f3385ca66d9a6f38f7e8c7e1ca17","permalink":"https://uw-echospace.github.io/author/brandon-reyes/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/brandon-reyes/","section":"authors","summary":"I truly believe that mathematics is a universal language that can solve some of the world’s most difficult problems! I also recognize that to accomplish these tasks, it is absolutely necessary to employ mathematical techniques in conjunction with software development and distributed computing.","tags":null,"title":"Brandon Reyes","type":"authors"},{"authors":["imranmaj"],"categories":null,"content":"I am a student at the University of Washington studying Electrical Engineering with a concentration in Embedded Computing Systems. I hope to graduate from the University of Washington in Spring/Fall of 2022. I enjoy programming and working with others to create better software.\nI am pursuing that passion in my position as a Student Assistant at the Applied Physics Laboratory where I am helping to develop Echopype, a tool for working with sonar data. Although I do not have much experience with acoustics, I enjoy learning more about this field every day.\nOther topics I am interested in are networking and server-side development. I am familiar with Python and Rust.\n","date":1651075800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1651075800,"objectID":"852c96dfdcbf495edc03de4ed7f060b1","permalink":"https://uw-echospace.github.io/author/imran-majeed/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/imran-majeed/","section":"authors","summary":"I am a student at the University of Washington studying Electrical Engineering with a concentration in Embedded Computing Systems. I hope to graduate from the University of Washington in Spring/Fall of 2022.","tags":null,"title":"Imran Majeed","type":"authors"},{"authors":["deryag"],"categories":null,"content":"Research Assistant I am an oceanographer and data scientist currently using Python to perform analysis on multi-year time-series data of seawater characteristics and sonar. I will also be helping conduct data and metadata organization and analysis of sonar observations from the NWFSC Pacific hake survey and use the echopype Python package to convert, quality assure, process, and visualize sonar data for distributed computing. In my free time, I enjoy writing for my blog about ocean data science, including write-ups of my projects and Python tutorials.\nI have experience in Python programming, data science, data analysis, data visualization, statistical modeling, machine learning, research, and science writing. I love learning and teaching others how to use Python to answer questions about the world with data.\nI earned my bachelor\u0026rsquo;s degree in oceanography from the University of Washington in 2020. During my time as a student, I enjoyed working part-time in ocean data analysis and visualization. After graduating, I pursued data science more seriously by completing an immersive data science certificate program through General Assembly. I\u0026rsquo;m excited to be applying my programming skills to real-world ocean data and contributing to research in both the oceanography and data science communities.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"150ee50ddafa7dcea4660e089d590c7b","permalink":"https://uw-echospace.github.io/author/derya-gumustel/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/derya-gumustel/","section":"authors","summary":"Research Assistant I am an oceanographer and data scientist currently using Python to perform analysis on multi-year time-series data of seawater characteristics and sonar. I will also be helping conduct data and metadata organization and analysis of sonar observations from the NWFSC Pacific hake survey and use the echopype Python package to convert, quality assure, process, and visualize sonar data for distributed computing.","tags":null,"title":"Derya Gumustel","type":"authors"},{"authors":["ngkavin"],"categories":null,"content":"I am a research assistant and software engineer focused on developing tools to assist with research in bioacoustics. Among other things, I have worked on the development of echopype, echoregions, GUIs for detecting and cleaning porpoise clicks, and scripts for converting and calibrating data provided by the Oceans Observatories Initiative (OOI) and the National Centers for Environmental Information (NCEI) data repositories.\nI recieved my bachelor\u0026rsquo;s degree in Applied Physics from the University of Washington, and will be returning this Fall to begin a master\u0026rsquo;s in Electrical Engineering.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"9003096bec37bf46c0cecf0289dd8466","permalink":"https://uw-echospace.github.io/author/kavin-nguyen/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/kavin-nguyen/","section":"authors","summary":"I am a research assistant and software engineer focused on developing tools to assist with research in bioacoustics. Among other things, I have worked on the development of echopype, echoregions, GUIs for detecting and cleaning porpoise clicks, and scripts for converting and calibrating data provided by the Oceans Observatories Initiative (OOI) and the National Centers for Environmental Information (NCEI) data repositories.","tags":null,"title":"Kavin Nguyen","type":"authors"},{"authors":["yjcheong"],"categories":null,"content":"I am interested in developing methods to enhance conventional acoustic sensing and imaging techniques. Nature provides a prime example of effective acoustic sensing through echolocation. By studying the processes and strategies used by echolocating animals to interpret acoustic information, we can gain insights into building more advanced acoustic systems. Additionally, I am interested in applying data-driven methods to acoustics, as these powerful tools can facilitate the discovery of many interesting phenomena.\nMy primary responsibilities within the group include:\n Developing physics-based models to study the complex interplay of sounds with the anatomical structures within the heads of toothed whales. This research aims to gain insights into how these interactions influence the whales' perception of sound, ultimately contributing to their exceptional abilities in detecting, localizing, and discriminating sounds.  ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"1ffb25ffb32e684ef207fc0ad5c53969","permalink":"https://uw-echospace.github.io/author/yeonjoon-cheong/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/yeonjoon-cheong/","section":"authors","summary":"I am interested in developing methods to enhance conventional acoustic sensing and imaging techniques. Nature provides a prime example of effective acoustic sensing through echolocation. By studying the processes and strategies used by echolocating animals to interpret acoustic information, we can gain insights into building more advanced acoustic systems.","tags":null,"title":"YeonJoon Cheong","type":"authors"},{"authors":["vms16"],"categories":null,"content":"I am a Senior Data Scientist and Data Science Fellow at the eScience Institute, Paul G. Allen School of Computer Science and Engineering, University of Washington. As part of my role I collaborate with researchers from a wide range of domains on extracting information from large data sets of various modalities, such as time series, images, videos, audio, text, etc. I am involved in data science education for audiences at broad level of experience, and regularly teach workshops on introductory and advanced topics. I support open science and reproducible research, and strive to help others adopt better data science workflows.\nResearch Interests:  Image Analysis Time Series Analysis Machine Learning for Ocean Acoustics Large Scale Computing Reproducible Research Workflows Data Science for Social Good  ","date":1740816e3,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1740816e3,"objectID":"130e266c25a4b00f04f02c9effe03d98","permalink":"https://uw-echospace.github.io/author/valentina-staneva/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/valentina-staneva/","section":"authors","summary":"I am a Senior Data Scientist and Data Science Fellow at the eScience Institute, Paul G. Allen School of Computer Science and Engineering, University of Washington. As part of my role I collaborate with researchers from a wide range of domains on extracting information from large data sets of various modalities, such as time series, images, videos, audio, text, etc.","tags":null,"title":"Valentina Staneva","type":"authors"},{"authors":["bmlucca"],"categories":null,"content":"Active acoustic backscatter is a powerful tool for quantifying spatiotemporal distributions of marine organisms ranging from shallow water estuaries to the dark depths of the bathypelagic ocean. This capability involves exploiting differences in organism-specific scattering properties to effectively fingerprint various types of scatterers (e.g., elastic-shelled pteropods, fish with gas-filled swimbladders) and estimating animal biomass (i.e., the number of animals). Despite its efficacy, acoustic classification and estimates of marine organisms can sometimes be imprecise, leading to substantial uncertainty. My primary focus is on quantifying the natural variability in the acoustic scattering properties of different organisms and understanding how this variability influences uncertainty estimates in target strength (i.e., the amount of backscatter from a single animal) and abundance/biomass. Additionally, I am interested in how various optimization and statistical techniques can be incorporated into forward and inverse problem modeling. Improving acoustic estimates of data products relevant to fishery/ecosystem managers can further help us discern how organisms react to environmental and hydrographic variability at both the individual and population levels.\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"56d11582f6cf9fb26f0f9cf77515ddea","permalink":"https://uw-echospace.github.io/author/brandyn-lucca/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/brandyn-lucca/","section":"authors","summary":"Active acoustic backscatter is a powerful tool for quantifying spatiotemporal distributions of marine organisms ranging from shallow water estuaries to the dark depths of the bathypelagic ocean. This capability involves exploiting differences in organism-specific scattering properties to effectively fingerprint various types of scatterers (e.","tags":null,"title":"Brandyn Lucca","type":"authors"},{"authors":["jgsachen"],"categories":null,"content":"I am a student at the University of Washington majoring in Molecular, Cellular, and Developmental Biology with a minor in Environmental Science and Resource Management. I am expected to graduate in the spring of 2023 and hope to one day attend graduate school to further my research.\nI am particularly interested in molecular ecology and population genetics of vulnerable species, and the effect climate change and human development will have on these populations. I am an avid outdoorswoman, and when you can\u0026rsquo;t find me in the lab I am usually hiking, camping, or birdwatching!\nAt Echospace, I am part of a team that studies local bat populations using bioacoustic data to better understand social and foraging behavior of bats.\nI am available via email, and happy to answer any questions you may have.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"85cd45957dab427e5a83a59f992008c0","permalink":"https://uw-echospace.github.io/author/josie-sachen/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/josie-sachen/","section":"authors","summary":"I am a student at the University of Washington majoring in Molecular, Cellular, and Developmental Biology with a minor in Environmental Science and Resource Management. I am expected to graduate in the spring of 2023 and hope to one day attend graduate school to further my research.","tags":null,"title":"Josie Sachen","type":"authors"},{"authors":["linda189"],"categories":null,"content":"I am a research assistant focused on the ADCP (Acoustic Doppler current profiler). I enjoy doing experiments and learning about acoustics. I had some experience with Python programming and I want to learn more. I earned my bachelor’s degree in applied physics from the University of Washington in 2021. I want to try out different fields, and I hope to return to school for a master\u0026rsquo;s degree.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"c7a4a0e7091e0f5b2dd1e457f00e2d34","permalink":"https://uw-echospace.github.io/author/linda-nguyen/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/linda-nguyen/","section":"authors","summary":"I am a research assistant focused on the ADCP (Acoustic Doppler current profiler). I enjoy doing experiments and learning about acoustics. I had some experience with Python programming and I want to learn more.","tags":null,"title":"Linda Nguyen","type":"authors"},{"authors":["liuyis"],"categories":null,"content":"I am a student at the University of Washington majoring in Statistics with a Data Science concentration. I expect to graduate in Spring 2025 and plan to pursue a graduate degree in Statistics or Data Science.\nI specialize in applying Python and R for data analysis. My hobbies are photography and composing.\nAt Echospace, I am working on the Bat Detector Validation Project. It is a manual calibration project that creates ground truth datasets for finetuning the batdetect2 (a deep learning model for detecting and classifying bat echolocation calls in high-frequency audio recordings) by manually labeling bat calls in RavenPro. I am also analyzing the effects of different environmental conditions on bat activity using statistical methods such as regression and ANOVA.\nIn addition, I am mainly in charge of weekly trips to the Union Bay Natural Area, deploying and recovering audiomoths (the acoustic loggers), then uploading the week\u0026rsquo;s data to the hard drive in the lab. I understand the importance of obtaining high-quality datasets for scientific research.\nIf you have any questions, please feel free to contact me via email.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"d4de73da4a91d0f1d2e4885d9e68f2d6","permalink":"https://uw-echospace.github.io/author/liuyixin-shao/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/liuyixin-shao/","section":"authors","summary":"I am a student at the University of Washington majoring in Statistics with a Data Science concentration. I expect to graduate in Spring 2025 and plan to pursue a graduate degree in Statistics or Data Science.","tags":null,"title":"Liuyixin Shao","type":"authors"},{"authors":["varkrish"],"categories":null,"content":"I am a student studying both Computer Science and Environmental Science at the University of Washington. I am expected to graduate in the summer of 2026.\nI have experience with a number of programming languages, including basic data analysis in R, some programming in Python, and extensive exposure making and manipulating data structures in Java, C, and C++.\nAs a recent addition to the Echospace team, I have small roles in a few different projects. I currently make weekly trips to Union Bay Natural Area to deploy and retrieve AudioMoth recorders. Additionally, I manually verify spectrogram bat calls marked by Machine Learning Algorithms as part of the Bat Detector Validation project. In the future, I hope to use echolocation data to determine behavioral patterns in bats in response to various environmental variables such as artificial lighting.\nPlease feel free to reach out to me via email if you have any questions!\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"c2ea56d07f787bdb160a83c253f8c00e","permalink":"https://uw-echospace.github.io/author/varun-krishnakumar/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/varun-krishnakumar/","section":"authors","summary":"I am a student studying both Computer Science and Environmental Science at the University of Washington. I am expected to graduate in the summer of 2026.\nI have experience with a number of programming languages, including basic data analysis in R, some programming in Python, and extensive exposure making and manipulating data structures in Java, C, and C++.","tags":null,"title":"Varun Krishnakumar","type":"authors"},{"authors":["ctuguina"],"categories":null,"content":"I am a recent graduate of the University of Washington. I majored in Mathematics and minored in Data Science. I am planning on pursuing graduate education in Statistics/Applied Mathematics.\nMy interests in applied math are in signal processing, specifically in the area of acoustics. My hobbies include running, swimming, and (very inconsistently) playing the piano.\nAt Echospace, I am working on the Hake Machine Learning (ML) Project.\nThe Hake ML Project is a Data Processing and Convolutional Neural Network project focused on the development of machine learning models for automatically detecting Pacific hake in large volumes of echosounder data.\nOne of the software packages I am developing and maintaining in this project is EchoRegions: A Python data processing software package to create region and bottom masks for echosounder data using both Echoview data and data products from Echopype.\nFor any inquiries, feel free to contact me via email!\n","date":1720732800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1720732800,"objectID":"1162cfb9b23dc89514e732bd96109f73","permalink":"https://uw-echospace.github.io/author/caesar-tuguinay/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/caesar-tuguinay/","section":"authors","summary":"I am a recent graduate of the University of Washington. I majored in Mathematics and minored in Data Science. I am planning on pursuing graduate education in Statistics/Applied Mathematics.\nMy interests in applied math are in signal processing, specifically in the area of acoustics.","tags":null,"title":"Caesar Tuguinay","type":"authors"},{"authors":["adkris"],"categories":null,"content":"I am a PhD student in the Electrical and Computer Engineering department at the University of Washington.\nMy interests are in utilizing ideas from statistics and signal processing to study how echolocating animals, such as bats and toothed whales, successfully perform complex tasks in dynamic environments.\nDuring my undergraduate studies, Wu-Jung and I led a long-term passive acoustic monitoring (PAM) program focused on capturing echolocation calls emitted by bats using autonomous recording units ( AudioMoths). We used the PAM data to perform an investigation into bat activity metrics and duty-cycle subsampling schemes.\nFeel free to ask me any questions at my email on doing research!\n","date":1715685e3,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1715685e3,"objectID":"c012ca76392ad2b45046e5904768ae37","permalink":"https://uw-echospace.github.io/author/aditya-krishna/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/aditya-krishna/","section":"authors","summary":"I am a PhD student in the Electrical and Computer Engineering department at the University of Washington.\nMy interests are in utilizing ideas from statistics and signal processing to study how echolocating animals, such as bats and toothed whales, successfully perform complex tasks in dynamic environments.","tags":null,"title":"Aditya Krishna","type":"authors"},{"authors":["alee2005"],"categories":null,"content":"Hi! I\u0026rsquo;m a senior at the University of Washington, studying Electrical and Computer Engineering with a focus on embedded systems. I love the ocean - I\u0026rsquo;m a team lead at UWROV, an underwater robotics team competing in the MATE Competition annually, and I enjoy scuba diving when I get the opportunity.\nI joined Echospace in the summer of 2024 and I\u0026rsquo;m excited to learn and showcase my skills. I\u0026rsquo;m currently developing a mobile weather station package with eventual near-real-time bat call detection to correlate weather data with bat calls to determine how bat activity varies with weather parameters.\nDon\u0026rsquo;t hesitate to reach out to me through email or through LinkedIn - I\u0026rsquo;d love to chat.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"5696b02da5e8521b337a103b54194ce7","permalink":"https://uw-echospace.github.io/author/aidan-lee/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/aidan-lee/","section":"authors","summary":"Hi! I\u0026rsquo;m a senior at the University of Washington, studying Electrical and Computer Engineering with a focus on embedded systems. I love the ocean - I\u0026rsquo;m a team lead at UWROV, an underwater robotics team competing in the MATE Competition annually, and I enjoy scuba diving when I get the opportunity.","tags":null,"title":"Aidan Lee","type":"authors"},{"authors":["amaj74"],"categories":null,"content":"I am a student at the University of Washington currently majoring in Mechanical Engineering with an expected graduation date in Spring of 2027. I have previously studied biology, and I enjoy connecting it with mechanical design to see them come together to create more efficient and innovative results.\nI do not have much prior experience with acoustics, but I am excited to learn about the subject as well as develop new skills. At Echospace, I am assisting with audio recorder deployments in the Union Bay Natural Area as well as with deployment of a microphone array to record bats.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"dd91851d31962e7fc4788ea858fce098","permalink":"https://uw-echospace.github.io/author/ameena-majeed/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/ameena-majeed/","section":"authors","summary":"I am a student at the University of Washington currently majoring in Mechanical Engineering with an expected graduation date in Spring of 2027. I have previously studied biology, and I enjoy connecting it with mechanical design to see them come together to create more efficient and innovative results.","tags":null,"title":"Ameena Majeed","type":"authors"},{"authors":["admin"],"categories":null,"content":"Our research focuses on active acoustic sensing by humans (machines) and animals. We integrate physics-based models with data-driven methods to extract information from large ocean acoustic datasets, and study echolocating bats and toothed whales as biological models for adaptive sonar sensing. In parallel, we develop open-source software and host hands-on workshops to engage and empower the community in advancing acoustic sensing technology.\nResearch areas:  Acoustical oceanography Fisheries acoustics Animal echolocation / bioacoustics Machine learning in ocean acoustics Scientific computing and software  ","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"https://uw-echospace.github.io/author/echospace/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/echospace/","section":"authors","summary":"Our research focuses on active acoustic sensing by humans (machines) and animals. We integrate physics-based models with data-driven methods to extract information from large ocean acoustic datasets, and study echolocating bats and toothed whales as biological models for adaptive sonar sensing.","tags":null,"title":"Echospace","type":"authors"},{"authors":null,"categories":null,"content":"Why  We respect and want to take advantage of the diversity of background and expertise in the group. We also want to create an optimal learning and research environment for everyone.  Code of Conduct Echospace is dedicated to providing a harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, or religion (or lack thereof). We do not tolerate harassment of group members in any form. Sexual language and imagery is not appropriate for any group venue, including meetings, presentations, or discussions, and in both physical and online spaces.\nWhat we value  Be proactive  Say hello to people you meet at work (in the morning when you come to work, etc) Be on time and respect other’s time, communicate if you don’t have time Don’t be afraid of being wrong and ask, and answer to questions from others kindly   Be open to change Communication  Respect other person’s background may be different from yours Be welcoming to others’ perspectives and what makes them tick, what excites them Don’t assume people know or don’t know what you’re talking about, it is ok and often better to just ask When there are different opinions, try to convince others by reasoning, and avoid being dismissive because of others’ career stages or rank Strive to communicate, both when we don’t think we understand what the other person is saying and when we think we are not being understood (misunderstandings) Acknowledge contributions from others   Ask questions and provide feedback kindly  Use “we” instead of “you” Use sandwich method: start with positive statement, follow with the comment “have you consider XYZ”, and end with positive affirmation/offer support Provide constructive feedback, elaborate on your comments, and be willing to explain more Value listening to others, and asking respectful questions Provide positive feedback too!   Group interaction and collaboration  Have clear expectations and communicate openly, to avoid last minute surprises Ensure everyone has the opportunity to participate both online and in person Give opportunities to others to speak first Make accommodations for personal emergencies   Help each other grow  Provide opportunities for peer mentoring Sharing opportunities in the group that others might be interested in (or would want to be involved in) Enable and encourage growth by everyone in the group, in directions that align with what they’re interested in Be comfortable bringing up issues or obstacles that hold you back from getting work done    Feedback Sharing Provide feedback on what to improve either in person or use the Echospace Anonymous Feedback Form if you prefer to remain anonymous. The form requires one to be logged with their uw email address, but we will not have access to it.\nConflict Resolution If you see something inappropriate, let Wu-Jung or Valentina know immediately, or contact the Office of the Ombud for support in conflict resolution. You can refer to some additional resources from the UW HR office here or refer to your department for advice.\n","date":1727568e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1727568e3,"objectID":"a259e2d98c97da77a38c46c2f9804fa8","permalink":"https://uw-echospace.github.io/group/coc/","publishdate":"2024-09-29T00:00:00Z","relpermalink":"/group/coc/","section":"group","summary":"We review and discuss our code of conduct and what we value regularly, as a reminder and inspiration.","tags":null,"title":"Code of Conduct \u0026 What we value","type":"group"},{"authors":null,"categories":null,"content":"Ocean acoustics is an interdisciplinary field in which researchers focus on measuring, modeling, and understanding acoustic phenomena of oceanographical, geological, biological, and anthropogenic sources. However, despite its inherent interdisciplinary nature, Ocean acoustics research currently has limited presence in most US institutions and is typically viewed as a highly niched field.\nThe Bridge to Ocean Acoustics and Technology (BOAT) program aims to broaden access to ocean acoustics by empowering learners to explore and advance the field through collaboration and shared knowledge, focusing on:\n Developing open, executable, and web-hosted tutorials that encapsulate fundamental ocean acoustics knowledge and techniques as living documents. Growing the ocean acoustics education and research community through interactive and collaborative workshops.  In the current pilot phase, we will host two education workshops to provide a hands-on introduction to ocean acoustics—from fundamental concepts to real-world applications—using interactive Jupyter notebooks. We will cover topics broadly applicable to both active and passive acoustics, with hands-on experience using echosounder and hydrophone datasets.\nOur goal is to create open tutorials that can 1) be adapted to various educational settings, including regular university courses or summer workshops, and 2) serve as blueprints for further developing in-depth resources on specific ocean acoustics topics.\nSee the BOAT website for information for the two upcoming workshops in Seattle and New Orleans!\nFunding Agency: Office of Naval Research, Ocean Acoustics Program\n","date":1711674156,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1711674156,"objectID":"a2d45828660b37781278922a84fae5e6","permalink":"https://uw-echospace.github.io/project/boat/","publishdate":"2024-03-28T17:02:36-08:00","relpermalink":"/project/boat/","section":"project","summary":"An open education program for ocean acoustics via executable tutorials","tags":["education","community engagement"],"title":"BOAT: Bridge to Ocean Acoustics and Technology","type":"project"},{"authors":null,"categories":null,"content":"As global warming accelerates and continues to reshape regional climates, changes in local weather patterns, such as rising temperatures, irregular rainfalls, and random forest fires, can profoundly alter bat behavior, foraging patterns, and migration timing, affecting the overall health of the entire bat communities. Therefore, understanding which environmental conditions have an impact on bat activity, and to what extent, is critical to developing effective conservation strategies in one region.\nWith the Union Bay Natural Area at the University of Washington as a research site, using bat echolocation call detections from the UBNA passive acoustic monitoring program, meteorological data from the University of Washington weather station, and lunar phase data from NASA, the project aims to find the environmental factors that influence bat activity and explore the effects of extreme stormy weather on local bat emergence through statistical testing and inference.\nFunding: UW Royalty Research Fund\n","date":1710550956,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1710550956,"objectID":"6af5808c437e5bbb8461c4efad2f5930","permalink":"https://uw-echospace.github.io/project_others/2024-ubna-weather/","publishdate":"2024-03-15T17:02:36-08:00","relpermalink":"/project_others/2024-ubna-weather/","section":"project_others","summary":"Analyzing the effects of weather factors on bat activity through ANOVA, negative binomial GLM, and DiD.","tags":["bat echolocation","environmental factor","statistics analysis"],"title":"Analyzing the effects of environmental conditions on bat activity","type":"project_others"},{"authors":null,"categories":null,"content":"Understanding how echolocators make use of sound to navigate their surroundings has great potential for informing the design of advanced acoustic sensing technologies. Although much has already been studied in laboratory experiments, technology has just started catching up to allow researchers to study echolocation-related processes in the wild. Advancements in passive acoustic monitoring tools have made it affordable to conduct long-term acoustic surveys on animals in the wild. Echolocators, like bats, are well-suited for monitoring using simple passive acoustic techniques because of their use of acoustics and navgitaion in air.\nIn this project, we sought to collect long-term acoustic data using Audiomoths from an urban natural area called the Union Bay Natural Area at the University of Washington. With this data, we hope to uncover questions on how environmental conditions influence how bats choose to forage.\nFunding agency: University of Washington Royalty Research Fund\n","date":1630544556,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1630544556,"objectID":"6c3ffff4eb79f0fdb09471a8b93900dc","permalink":"https://uw-echospace.github.io/project_others/2022-ubna-pam/","publishdate":"2021-09-01T17:02:36-08:00","relpermalink":"/project_others/2022-ubna-pam/","section":"project_others","summary":"Using passive acoustic techniques to study bat foraging behaviors in an urban natural area","tags":["bat echolocation","passive acoustics","community engagement"],"title":"UBNA passive acoustic monitoring project","type":"project_others"},{"authors":null,"categories":null,"content":"Passive acoustic monitoring (PAM) has become a useful technique for monitoring soniferous animals in both terrestrial and marine habitats, and has in recent years been particularly bolstered by the broader availability and accessibility of low-cost recording devices.\nIn this project, we deploy low-cost AudioMoth recorders at multiple sites in the Union Bay Natural Area, right on the eastern edge of the University of Washington, Seattle campus. Since the project began in fall 2021, we have collected over 30 TB of recordings that are embedded with sounds from a wide variety of animals (e.g., birds, bats, frogs) and anthopogenic sources (e.g., airplanes, football stadium roars).\nBeyond generating a rich dataset, the project fieldwork and data analysis provides an accesible entry point for students to engage in real-world bioacoustics research, with hands-on data science and instrumentation opportunities.\nWe have leveraged this dataset to investigate the impact of duty cycle recording on bat monitoring and support multiple capstone projects in the UW Data Sciene Master\u0026rsquo;s Program, focused on developing open-source, cloud-hosted workflows for analyzing large PAM datasets. With these tools in place, going forward we plan to characterize the seasonal soundscape fluctuations in UBNA with respect to weather/climate events, and find opportunities to expand this effort to a community monitoring program in the Greater Seattle area.\n Bat call activity detected in two UBNA sites in 2022. Funding: UW Royalty Research Fund\n","date":1630454400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1630454400,"objectID":"fb47fbc42077831f306640729157c7f5","permalink":"https://uw-echospace.github.io/project/ubna-pam/","publishdate":"2021-09-01T00:00:00Z","relpermalink":"/project/ubna-pam/","section":"project","summary":"Using passive acoustic techniques to monitor bats and birds on UW campus!","tags":["echolocation","passive acoustic monitoring","community engagement"],"title":"Passive acoustic monitoring in the Union Bay Natural Area","type":"project"},{"authors":null,"categories":null,"content":" Active acoustic data collected by echosounders (high-frequency sonar systems) play a crucial role in marine ecological research and fisheries stock assessments. Recent technical advancements has further integrated echosounders onto many ocean observing platforms, leading to the rapid accumulation of echosounder data worldwide.\nIn this project, we tackle the challenge of translating experiences from human experts into machine learning models capable of efficiently extracting biological information from large echosounder dataset. Using the rich dataset collected by the Joint U.S.-Canada Integrated Ecosystem and Pacific Hake Acoustic Trawl Survey dated back to early 2000s, we are developing deep learning models to automatically annotate echograms—color-coded visual representations of echo returns—with the presence of specific fish and zooplankton species or taxa.\nIn the first stage of the project, we are focusing on developing an echogram segmentation model to identify Pacific hake, a keystone species and the largest fishery stock on the west coast of the US. Identifying hake on echograms is more challenging compared to many other fish species, due to their polymorphic appearance and diffused school boundaries. We found that neural networks' large learning capacity are well-suited to address these complexities. However, as in many other domains, organizing echosounder data with survey metadata and sorting expert annotations remains a significant bottleneck in fully leveraging these technologies.\nMoving forward, we aim to expand the model to include other ecologically and commercially important fish species in the California Current ecosystem, and incorporate other analytical methods, such as Bayesian inversion techniques, to improve acoustic data interpretation and biomass estimation accuracy.\n--  Echogram examples showing the deep learning model predicts regions similar to human expert annotations. This project is in close collaboration with the Fisheries Engineering and Acoustics Technology (FEAT) team at the NOAA Fisheries Northwest Fisheries science center (NWFSC).\nFunding agency: NOAA Fisheries\n","date":1619917356,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1619917356,"objectID":"162b07855430499dd877a9058fdd9e34","permalink":"https://uw-echospace.github.io/project/hake-ml/","publishdate":"2021-05-01T17:02:36-08:00","relpermalink":"/project/hake-ml/","section":"project","summary":"Accelerating information extraction from fisheries acoustic data through a cloud-based machine learning workflow.","tags":["machine learning","fisheries acoustics","cloud computing"],"title":"Machine learning in fisheries acoustics","type":"project"},{"authors":null,"categories":null,"content":"Scientists commonly use active sonar systems to collect data about mid-trophic level animals like zooplankton and small fish, which play an important role in the marine ecosystems. Echosounders, or fish-finders, are high-frequency sonar systems that emit pulses of sound and record the reflections from animals, the seabed, and other objects. These instruments have been proven to be more efficient and effective for collecting data over a large survey area or a long time period than many other sampling methods, such as underwater imaging and net trawls. This technology has been widely adopted by the ocean science and commercial fishing communities and more recently has been integrated with autonomous vehicles, resulting in a massive amount of data. However, these datasets can be difficult to analyze and are often underutilized. We will address this issue by adopting and advancing data standards, developing a streamlined data processing workflow, and integrating open-source software tools that capitalize on recent advancements in cloud computing technologies to efficiently transform large quantities of ocean sonar data into information that is useful for exploring, monitoring, and managing living marine resources.\nFunding agency: NOAA Office of Ocean Exploration and Research FY2021 grants\n","date":1635123396,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1635123396,"objectID":"00c625a176bf2bcf2b303c7d64bb113b","permalink":"https://uw-echospace.github.io/project_others/2021-cloud-workflows/","publishdate":"2021-10-24T16:56:36-08:00","relpermalink":"/project_others/2021-cloud-workflows/","section":"project_others","summary":"Accelerating ocean exploration through cloud-native processing of active ocean sonar data.","tags":["fisheries acoustics","cloud computing","community engagement"],"title":"Scalable, cloud-native processing of water column sonar data","type":"project_others"},{"authors":null,"categories":null,"content":" Water column sonar data collected by echosounders are essential for fisheries and marine ecosystem research, enabling the detection, classification, and quantification of fish and zooplankton from many different ocean observing platforms. However, the broad usage of these data has been hindered by the lack of modular software tools that allow flexible composition of data processing workflows that incorporate powerful analytical tools in the scientific Python ecosystem.\nWe address this gap by developing Echostack, a suite of open-source Python software packages that leverage existing distributed computing and cloud-interfacing libraries to support intuitive and scalable data access, processing, and interpretation. These tools can be used individually or orchestrated together, which we demonstrate in example use cases for a fisheries acoustic-trawl survey.\nBelow is a summary of the Echostack packages:\n For more information, check out the code repositories below:\n  Echopype  Check out the our Echopype paper in the ICES Journal of Marine Science    Echopop  Learn more on the Echopop project page    Echoshader  Echoregions  Echodataflow  These packages are accompanied by a set of Echolevels that categorize data products at different workflow stages to enhance data understanding and provenance tracking.\nCheck out Wu-Jung\u0026rsquo;s talk at SciPy 2024 and the associated paper in the proceedings!   Funding:\n NOAA Fisheries NOAA Office of Ocean Exploration and Research FY2021 grants  ","date":1625097600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1625097600,"objectID":"38ca87fb3057d53887ebed5b2061daa2","permalink":"https://uw-echospace.github.io/project/echostack/","publishdate":"2021-07-01T00:00:00Z","relpermalink":"/project/echostack/","section":"project","summary":"Enhancing the processing capacity and efficiency for echosounder data.","tags":["fisheries acoustics","cloud computing","open-source","community engagement"],"title":"The open-source \"Echostack\" for flexible and scalable echosounder data processing","type":"project"},{"authors":null,"categories":null,"content":"Echopop is a software used for processing backscatter measurements and biological data collected from acoustic-trawl surveys to estimate population estimates and other metrics. The development of this software has been primarily focused on surveys targeting Pacific hake (see below information for more details), but the goal is to generalize the software in the future for broader fisheries community use.\nThe Fisheries Engineering and Acoustics Technology (FEAT) team at the NOAA Fisheries Northwest Fisheries Science Center (NWFSC) collaborates with Fisheries and Oceans Canada (DFO) - Pacific Region to estimate total biomass of Pacific hake (Merluccius productus) by incorporating acoustic and biological trawl data from the Joint U.S.-Canada Integrated Ecosystem and Pacific Hake Acoustic-Trawl Survey (aka the \u0026ldquo;Hake survey\u0026rdquo;).\nThese biomass estimates are the inputs for the stock assessment of hake and need to be completed in an efficient and timely manner after the survey. The biomass estimates are currently produced by a suite of Matlab scripts operated by a single user, and the analysis procedures are not easily adaptable by other FEAT/DFO team members. The central objective of this project is to provide a well-documented open-source Python software package (echopop) that contains the core computational functionality of the current Matlab EchoPro program and provides basic visualization of the analysis results.\nThe new software package (currently version 0.4.0 and available on PyPi) contains an expanded documentation that details the underlying theory and algorithmic implementation that help facilitate reproducibility. Other features include an Application Programming Interface (API) that can be invoked in a reproducible manner, a flexible analysis configuration that allows for both machine and human-readable parameterizations, and interactive Jupyter notebooks that exemplify various workflows ranging from initial data processing to kriging.\nFunding agency: NOAA Fisheries, NOAA NWFSC\n","date":1643158956,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1643158956,"objectID":"a703c553a7a2ee2ff30efaf9d148ec4c","permalink":"https://uw-echospace.github.io/project_others/echopop/","publishdate":"2022-01-25T17:02:36-08:00","relpermalink":"/project_others/echopop/","section":"project_others","summary":"Integrating echosounder data and net catches for biomass estimation.","tags":["fisheries acoustics","scientific computing","open-source"],"title":"Echopop: biomass estimation for Pacific Hake","type":"project_others"},{"authors":null,"categories":null,"content":"General information We welcome researchers and students with diverse backgrounds to come work with us in Echospace! If you don\u0026rsquo;t see a specific position below, feel free to reach out to us directly. Please include a cover letter and a CV/resume when initiating the contact, so that we have a better idea what you are looking for and your background.\nFellowship opportunities Below is a list of fellowship opportunities within and outside of UW. Relevant areas include but are not limited to fisheries and ocean acoustics, animal echolocation (bats and dolphins), marine ecology, and environmental data science. Feel free to reach out to us for questions and discussion.\nPostdoc fellowships University of Washington   APL SEED Postdoctoral Scholar Program  Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES) postdoctoral fellowship  Washington Research Foundation (WRF) Postdoctoral Fellowship  External   NSF Ocean Sciences (OCE) Postdoctoral Research Fellowships (OCE-PRF)  NSF Division of Earth Sciences (EAR) Postdoctoral Fellowships (EAR-PF)  Acoustical Society of America (ASA) F. V. Hunt Postdoctoral Research fellowship  Graduate fellowships   NSF Graduate Research Fellowships Program (GRFP)  Undergraduate fellowships   UW Mary Gates Research Scholarship  APL DINO-SIP Diverse + Inclusive Naval Oceanographic Summer Intership Program  ","date":1725148800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1725148800,"objectID":"c06930b45ea7db1583d86ce110d917ae","permalink":"https://uw-echospace.github.io/position/opportunities/","publishdate":"2024-09-01T00:00:00Z","relpermalink":"/position/opportunities/","section":"position","summary":"Interested in joining Echospace? Check out the latest info here!","tags":null,"title":"Opportunities at Echospace","type":"position"},{"authors":null,"categories":null,"content":"Mid-trophic level animals, such as zooplankton and fish, are keystone organisms in the marine ecosystem and play a critical role in the economy and our food supply chain. However, our understanding of these animals, particularly those in the pelagic zones, is severely limited, due to the lack of tools that cab . This gap of knowledge has greatly impeded our ability in making informed policy decisions to support sustainable resource management. The root cause of this problem is the lack of tools that can collect information about these animals at large temporal and spatial scales comparable to other physical, chemical, and lower-trophic biological (e.g., chlorophyll) oceanographic variables.\nGliders have provided unparalleled mobile, persistent access to deep, remote ocean environments at a fraction of the cost of a research vessel. Taking advantage of this unique capability, in this project we aim to develop sampling strategies and data analysis methodologies to enable distributed long-term observation of mid-trophic marine organisms using Seagliders equipped with acoustic Doppler current profilers (ADCPs).\nFunding agency: NOAA Office of Ocean Exploration and Research FY2020 grants\n","date":1599008556,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1599008556,"objectID":"8994a4616f45f3e1fc1c9448ae66b613","permalink":"https://uw-echospace.github.io/project/2020-glider-adcp/","publishdate":"2020-09-01T17:02:36-08:00","relpermalink":"/project/2020-glider-adcp/","section":"project","summary":"Enabling distributed, persistent observation of mid-trophic zooplankton and fish using autonomous underwater gliders equipped with acoustic Doppler current profilers (ADCPs).","tags":["glider","ADCP","fieldwork","distributed sensing"],"title":"ADCP-equipped underwater glider as a distributed biological sensing tool","type":"project"},{"authors":null,"categories":null,"content":"In this collection we share useful starting computing resources among echospace group members.\n  Conda and Jupyter  Git and GitHub  Cloud computing  HPC and SLURM  OSN data access  Other topics to be covered  ","date":1701907200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1701907200,"objectID":"98589b7307ad5bff51e8120890854848","permalink":"https://uw-echospace.github.io/group/compute_docs/","publishdate":"2023-12-07T00:00:00Z","relpermalink":"/group/compute_docs/","section":"group","summary":"Useful starting computing resources","tags":null,"title":"Computing startup resources","type":"group"},{"authors":null,"categories":null,"content":"Echopype is an open-source Python package aimed at enhancing the interoperability and scalability in processing ocean sonar data for biological information.\nI started building this package in early 2018 when I couldn\u0026rsquo;t find an affordable tool that allow easy access and manipulation of echosounder data collected by different sonar models.\nFor the latest updates, check out our repo at: https://github.com/OSOceanAcoustics/echopype.\nCheck out my talk at SciPy 2019 that discussed the goals and philosophy of echopype:   ","date":1604271e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1604271e3,"objectID":"b8a6b0614ce7d7e0aecef44c5345caf8","permalink":"https://uw-echospace.github.io/project_others/echopype/","publishdate":"2020-11-01T14:50:00-08:00","relpermalink":"/project_others/echopype/","section":"project_others","summary":"A Python package that enhances the interoperability and scalability in ocean sonar processing.","tags":["fisheries acoustics","scientific computing","open-source"],"title":"Echopype","type":"project_others"},{"authors":null,"categories":null,"content":"Funding agency: National Science Foundation Award #1849930\n","date":1546383e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1546383e3,"objectID":"57140da2fed4b9554ced204c75c7a02a","permalink":"https://uw-echospace.github.io/project/2019-ooi-mtx-decomp/","publishdate":"2019-01-01T14:50:00-08:00","relpermalink":"/project/2019-ooi-mtx-decomp/","section":"project","summary":"Developing algorithms to discover prominent spatio-temporal patterns of animal movement and grouping behavior observed in sonar echoes using data from the Ocean Observatories Initiative (OOI).","tags":["machine learning","OOI","fisheries acoustics"],"title":"Pattern discovery from long-term echosounder time series","type":"project"},{"authors":null,"categories":null,"content":"For a 2018 tutorial I published with Tim Stanton and Kyungmin Baik in the Journal of the Acoustical Society of America (JASA):\nEcho statistics associated with discrete scatterers: A tutorial on physics-based methods. JASA 144(6): 3124–3171; https://doi.org/10.1121/1.5052255\nwe provided the Matlab code to reproduce all figures in two forms:\n a frozen version archived with the paper, and a GitHub repository minted with a DOI from Zenodo.  This way we can keep the code \u0026ldquo;alive\u0026rdquo; on GitHub but also has a convenient snapshot of the code at the time of the tutorial publication.\n","date":1543651200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1543651200,"objectID":"992ae35a85278cc48681a9f5526b3b73","permalink":"https://uw-echospace.github.io/project/echo-stat-tutorial/","publishdate":"2018-12-01T00:00:00-08:00","relpermalink":"/project/echo-stat-tutorial/","section":"project","summary":"Matlab code to reproduce all figures in an in-depth tutorial on echo statistics.","tags":["matlab","open-source","echosounder"],"title":"Echo Statistics","type":"project"},{"authors":null,"categories":null,"content":"Toothed whales, including species such as porpoises, dolphins, orca, and sperm whale, possess highly specialized anatomical structures in the head to support their biosonar systems - echolocation - through millions of years of evoluation. These animals have the remarkable ability to detect and track small targets over long distance and discriminate between minute differences between targets using echolocation, with performance often surpassing that of current human-made sonar systems. However, many questions remain in how exactly the unusual anatomical structures in the head of toothed whales are orchestrated to support such performance.\nAs part of a Multidisciplinary University Research Initiative (MURI) project, we use finite element modeling techniques in combination with volumetric representations derived from computed tomography (CT) scans to predict the head-related transfer functions (HRTFs) of a dolphin head. The HRTFs summarizes the influence of the head to sounds propagating to the ears. We use HRTFs as a biologically meaningful proxy to provide a physics-based mechanistic understanding of the sound transduction processes.\nFunding: Office of Naval Research, Multidisciplinary University Research Initiative (MURI) program\n","date":1656633600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1656633600,"objectID":"8d3bb786cbbd21a856f4e3fd0a5588c4","permalink":"https://uw-echospace.github.io/project/echolocation-comsol/","publishdate":"2022-07-01T00:00:00Z","relpermalink":"/project/echolocation-comsol/","section":"project","summary":"Understanding the interaction of sound with biological structures in toothed whale head.","tags":["echolocation","finite element modeling"],"title":"Modeling sound propagation in the head of toothed whales","type":"project"},{"authors":null,"categories":null,"content":"Echolocating animals effortlessly navigate, hunt, and interact with their environment, despite cluttered and noisy return signals. Blind expert human echolocators prove that this capacity does not depend exclusively on biological specializations unique to particular species. This project is an integrated component of a larger collaborative Multidisciplinary University Research Initiative (MURI) project focused on active sensing in echolocating marine mammals and humans. The MURI team use both toothed whales (odontocetes) and humans as model systems to identify the neural mechanisms that extract echo-acoustic information and the brain networks that build and learn robust, invariant representations of auditory objects in complex auditory scenes.\nIn Echospace, we undertake two interconnected components of this project:\n Model the echolocation-based target search by toothed whales as an information-seeking behavior by extending the infotaxis algorithm originally formulated in moth odor tracking problems into an active sensing context   Conduct and analyze the coupled acoustic sampling and movement behaviors of an echolocating harbor porpoise in a target discrimination experiment  Funding agency: Office of Naval Research, Multidisciplinary University Research Initiative (MURI) program\n","date":2018,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":2018,"objectID":"5f29bbd0450b220f203170fafa35e702","permalink":"https://uw-echospace.github.io/project/echolocation-search/","publishdate":"1970-01-01T00:33:38Z","relpermalink":"/project/echolocation-search/","section":"project","summary":"Modeling and analyzing the echolocation behavior of toothed whales.","tags":["echolocation","infotaxis"],"title":"Target search and discrimination by echolocating toothed whales","type":"project"},{"authors":null,"categories":null,"content":"Mode of Communication We use various modes of communication in Echospace to keep ourselves up-to-date on what we are each working on and coordinate.\nDepending on who\u0026rsquo;s involved and the context, we use different methods to communicate. In general:\n Internal (among group members): mostly Slack External (with colleagues outside of the group): emails GitHub: PR and issues, see here for how to get started Talking: we do talk in analog form!  Expectations  We encourage proactive and frequent communication; for most projects we meet at least weekly to keep each other updated and set short and long term goals Immediate response are not expected unless urgent People may send messages/emails at their convenient time; aim to respond within a reasonable time frame Phone/text: usually reserved for urgent communication or offsite coordination Ask us/everyone for help, and provide help if you can!  Slack workspace  Default channels you\u0026rsquo;re added to:  #general #help #random   Feel free to:  Add or remove yourself from channels, but make sure you stay in the know for your projects, as well as group announcements Create new channels and announce in the #general channel for others to join    ","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"e80b9d7a87c9a7b05871cf51e62213c9","permalink":"https://uw-echospace.github.io/group/communication/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/group/communication/","section":"group","summary":"Our current practice to communicate with each other in Echospace","tags":null,"title":"Communication within group","type":"group"},{"authors":["**A Krishna**","W-J Lee"],"categories":["echolocation"],"content":"","date":1757376e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1757376e3,"objectID":"052463869c99cebfcb870a9b094efc7e","permalink":"https://uw-echospace.github.io/publication/2025-krishna-lee-jasa-dutycycle/","publishdate":"2025-09-12T00:00:00Z","relpermalink":"/publication/2025-krishna-lee-jasa-dutycycle/","section":"publication","summary":"We performed a systematic investigation into the effects of duty-cycling on measuring activity in the passive acoustic monitoring of echolocating bats.","tags":["passive acoustic monitoring","echolocation"],"title":"Influence of duty-cycle recording on measuring bat activity in passive acoustic monitoring","type":"publication"},{"authors":["**Y Cheong**","W-J Lee","A Ruesch","MD Schalles","J Kainerstorfer","B Shinn-Cunningham"],"categories":["echolocation"],"content":"","date":1751932800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1751932800,"objectID":"a786a69858df64247d057d55f28f3fa3","permalink":"https://uw-echospace.github.io/publication/2025-cheong-etal-jasa-hrtf/","publishdate":"2025-09-12T00:00:00Z","relpermalink":"/publication/2025-cheong-etal-jasa-hrtf/","section":"publication","summary":" ","tags":["echolocation"],"title":"Head-related transfer function predictions reveal dominant sound propagation mechanisms to the dolphin ears","type":"publication"},{"authors":["**W-J Lee**","M Ladegaard","MD Schalles","JR Buck","K Beedholm","PT Madsen","PL Tyack"],"categories":["echolocation"],"content":"","date":1751846400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1751846400,"objectID":"a4877ff69566c97ea68534d8e7b74cf3","permalink":"https://uw-echospace.github.io/publication/2025-lee-etal-jasa-porpoise-movement/","publishdate":"2025-09-12T00:00:00Z","relpermalink":"/publication/2025-lee-etal-jasa-porpoise-movement/","section":"publication","summary":" ","tags":["echolocation"],"title":"Movement trajectories reflect active information acquisition by an echolocating porpoise in a target discrimination task","type":"publication"},{"authors":["Wu-Jung Lee","Valentina Staneva"],"categories":null,"content":"Open-Source Software to Accelerate Marine Ecosystem Research The Echospace research group at the University of Washington, Seattle is seeking a highly motivated individual to contribute to the development of cutting-edge software tools for marine ecosystem research. This position offers the opportunity to work on \u0026ldquo; Echostack\u0026rdquo;, a suite of open-source Python software packages designed to process and analyze large-scale echosounder data.\nEchosounders are high-frequency ocean sonar systems widely used to study life in the ocean. By transmitting sounds and analyzing the echoes bounced off fish and zooplankton, echosounders “image” the underwater world much like how medical ultrasound images the interior of the human body, providing crucial insights into marine ecosystems. By joining this project, you will play a key role in making echosounder data more accessible and useful for researchers worldwide.\nWhat you’ll do  Design, develop, and test open-source software for processing and analyzing large volumes of echosounder data Optimize and benchmark software performance on local computers and cloud virtual machines Process and analyze archived echosounder data spanning over 20 years, collected by NOAA and other US institutions Build and manage near real-time data workflows from research cruises  Who we’re looking for We welcome applications from recent graduates, post-baccalaureate researchers, advanced undergraduates, or current master’s students with the following qualifications:\n A solid foundation in software engineering Proficiency with object-oriented programming, particularly in Python Experience with or a strong interest in large datasets and distributed computing Completion of a college level linear algebra course Commitment to learn echosounder data processing procedures and data structures A strong interest in ocean science, environmental science, or related fields Excellent communication skills to work effectively in an interdisciplinary team of researchers with backgrounds in engineering, mathematics, and biology  Note this position is intended for early career professionals or students. The initial appointment will be 3-6 months with a possibility of extension. The exact position setup will vary depending on your status.\nWhy join us? This is an excellent opportunity to:\n Develop open-source software that directly contributes to ocean research Gain experience in scientific computing, cloud computing, and environmental data science Work closely with researchers at the University of Washington, NOAA, and other institutions Build your technical portfolio and establish connections in the ocean technology and research community  Resources  UW Echospace: https://uw-echospace.github.io/ Echostack Talk at SciPy 2024: Watch here Echostack Paper: Read here Introduction to echosounder data: StoryMap  How to Apply To apply, email Dr. Wu-Jung Lee (leewj@uw.edu) and Dr. Valentina Staneva (vms16@uw.edu) with the following:\n A cover letter detailing:  Why you believe you are a good fit for this role How this position aligns with your career goals or research interests Any relevant prior experiences Timeframe and capacity (part-time/full-time) you are available for this position   A CV or resume that includes a link to your GitHub account (or equivalent portfolio) showcasing your previous software work.  If your past contributions are only available in private repositories, please provide a detailed project description or create a public example that highlights your skills.\n","date":1740816e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1740816e3,"objectID":"3488fb2ff59cfe78c8c341e0ed584ad9","permalink":"https://uw-echospace.github.io/position/2025-03-01-rse/","publishdate":"2025-03-01T00:00:00-08:00","relpermalink":"/position/2025-03-01-rse/","section":"position","summary":" ","tags":null,"title":"Scientific Software Engineering Opportunity","type":"position"},{"authors":["W-J Lee","L Setiawan","C Tuguinay","E Mayorga","V Staneva"],"categories":["sonar"],"content":"","date":1728432e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1728432e3,"objectID":"72c9a9dd2909ce0cafce6aa36bc033ff","permalink":"https://uw-echospace.github.io/publication/2024-lee-etal-echopype/","publishdate":"2020-10-09T00:00:00Z","relpermalink":"/publication/2024-lee-etal-echopype/","section":"publication","summary":" ","tags":["open-source","fisheries acoustics","scientific computing","community engagement"],"title":"Interoperable and scalable echosounder data processing with Echopype","type":"publication"},{"authors":["Wu-Jung Lee","Valentina Staneva","Don Setiawan","Emilio Mayorga","Caesar Tuguinay","Soham Kishor Butala","Brandyn Lucca","Dingrui Lei"],"categories":null,"content":"","date":1720732800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1720732800,"objectID":"6281a726a84ebff1fcd2000beca01562","permalink":"https://uw-echospace.github.io/talk/202407-scipy-echostack/","publishdate":"2024-07-11T14:20:00-07:00","relpermalink":"/talk/202407-scipy-echostack/","section":"talk","summary":"Water column sonar data collected by echosounders are essential for marine ecosystem research, allowing the detection, classifi cation, and quantification of fish and zooplankton from many different ocean observing platforms. However, broad usage of these data has been hindered by the lack of software tools that allow intuitive and transparent data access, processing, and interpretation. We address this gap by developing Echostack, a toolbox of open-source packages leveraging distributed computing and cloud-interfacing libraries in the scientific Python ecosystem. These tools can be used individually or orchestrated together, which we will demonstrate in an end-to-end workflow.","tags":["open-source","pipeline","fisheries acoustics","scientific computing","data standard","community engagement"],"title":"Echostack: An open-source Python software toolbox that democratizes water column sonar dataand processing","type":"talk"},{"authors":["Aditya Krishna","Wu-Jung Lee"],"categories":null,"content":"","date":1715685e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1715685e3,"objectID":"153ac03cc329dcb71e6aaac047677431","permalink":"https://uw-echospace.github.io/talk/202405-aditya-duty-cycle/","publishdate":"2024-05-14T10:10:00-01:00","relpermalink":"/talk/202405-aditya-duty-cycle/","section":"talk","summary":" ","tags":["passive acoustic monitoring","bioacoustics","machine learning"],"title":"Investigation of duty cycles for measuring activity in passive acoustic bat monitoring","type":"talk"},{"authors":["Wu-Jung Lee","Valentina Staneva","Caesar Tuguinay"],"categories":null,"content":"","date":1715558400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1715558400,"objectID":"98b07dd9cd0f355299b3f1fe50201b41","permalink":"https://uw-echospace.github.io/talk/202405-asa-ottawa-hake/","publishdate":"2024-05-13T00:00:00Z","relpermalink":"/talk/202405-asa-ottawa-hake/","section":"talk","summary":"High-frequency echosounders are the workhorse in fisheries and marine ecological surveys. Due to the inherent complexity of biological aggregations and ambiguity in interpreting echoes from species of similar size and anatomical compositions, echogram annotation typically requires combining spectral information referencing scattering physics, biological ground-truth from nearby net-trawls, and empirical school morphology of specific fish species. Here, we investigate the variability of echogram annotations and its influence on machine learning applications using data from the biennial Pacific hake acoustic-trawl survey. Compared to many other fish species, hake tend to possess less defined school boundaries with variable acoustic features and often form mixed-species aggregations in the mesopelagic. Nonnegative matrix factorization and hierarchical clustering of volume backscattering strength (Sv) distributions across the 18, 38, and 120 kHz channels revealed a spectrum of annotation region types that reflect differences in morphological and acoustic features as well as differences in annotator style. This variability likely contributes to the observed variable segmentation behavior of deep learning models trained using this dataset. These results highlight the importance of considering the diversity of echogram annotation, its connection to scattering physics and the underlying aggregation composition, and the incorporation of such information in developing machine learning models.","tags":["fisheries acoustics","machine learning"],"title":"Variability and influence of fisheries acoustic echogram annotations on machine learning applications","type":"talk"},{"authors":["Wu-Jung Lee"],"categories":null,"content":"","date":1715472e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1715472e3,"objectID":"b82c7b4f4c1a1e8edc71d1072ba5557b","permalink":"https://uw-echospace.github.io/talk/202405-asa-ottawa-school/","publishdate":"2024-05-12T00:00:00Z","relpermalink":"/talk/202405-asa-ottawa-school/","section":"talk","summary":"In this presentation, I will discuss fundamental concepts of using active acoustic techniques as a remote sensing tool to observe mid-trophic level fish and zooplankton in the ocean. These observations complement passive acoustic measurements that tend to capture activities of higher trophic level animals, such as marine mammals. I will introduce physics-based acoustic scattering models and their use in interpreting active acoustic data (the echoes), and discuss recent advancements in incorporating data science techniques, including machine learning, to extract information from the rapidly growing volumes of active acoustic data around the world. Following this discussion, I will share a few tips for implementing best practices in reproducible research and scientific software development, and invite participants to anonymously share their thoughts and experiences on these topics in the fields of acoustics.","tags":["fisheries acoustics","machine learning","scientific computing","open-source"],"title":"Two Pieces of the Same Puzzle: Active and Passive Acoustics for Cross-Trophic Marine Ecosystem Monitoring Part II","type":"talk"},{"authors":["Wu-Jung Lee","Valentina Staneva","Dingrui Lei","Zhongqi Miao"],"categories":null,"content":"","date":1712844e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1712844e3,"objectID":"e721eb3306b944cafaa06d721b9331a8","permalink":"https://uw-echospace.github.io/talk/202404-wgfast-ship2cloud/","publishdate":"2024-04-11T09:00:00-05:00","relpermalink":"/talk/202404-wgfast-ship2cloud/","section":"talk","summary":"Successful application of machine learning (ML) methodology requires iterative development and testing of not only the models but also the entire workflow on the very platform and operating scenario the development aims to serve, before the framework is generalized to other settings. In this work we present our implementation of a ship-to-cloud ML pipeline during the 2023 Pacific hake acoustics-trawl survey. Hake is a keystone species in the northern California Current ecosystem and supports the largest fishery on the west coast of the U.S. By integrating an echogram semantic segmentation model targeting hake with the “Echostack” suite of open-source Python software packages, our pipeline transformed raw instrument-generated binary files into hake aggregation predictions, which were displayed in two ways: in a configurable Python dashboard that allows sharing widely with collaborators, and in Echoview for aligning with live screening. We transmitted data products with reduced resolution and the corresponding ML predictions to the cloud in sub-realtime, allowing shore-side interaction. We plan to incorporate biomass estimation based on initial fish biometric measurements, automate the orchestration of this ship-to-cloud pipeline, and prototype an ML-driven annotation framework in the future.","tags":["open-source","pipeline","fisheries acoustics","scientific computing","data standard","community engagement"],"title":"A ship-to-cloud machine learning pipeline built on the open-source Python Echostack software tools","type":"talk"},{"authors":["Valentina Staneva","Soham Kishor Butala","Wu-Jung Lee","Don Setiawan"],"categories":null,"content":"","date":1712844e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1712844e3,"objectID":"5913d6e7a4c2e5cf68fdefacd16e01b6","permalink":"https://uw-echospace.github.io/talk/202404-wgfast-echodataflow/","publishdate":"2024-04-11T09:00:00-05:00","relpermalink":"/talk/202404-wgfast-echodataflow/","section":"talk","summary":"Acoustic fisheries surveys and ocean observing systems collect terabytes of echosounder data that require custom processing pipelines to obtain biological estimates of target species, which often can be hard to reuse or adapt. There is a rising need to scale computations on local and cloud computing clusters. However, this requires an elaborate configuration of computing infrastructure and distributed computing libraries, and the ability to monitor progress and performance.\nIn this talk, we describe how we address some of these challenges by developing a framework that allows researchers to execute complex echosounder data processing procedures on both local and cloud platforms by editing text-based configuration “recipe” templates. We create a user-friendly Python package Echodataflow that leverages Prefect, a modern workflow orchestration framework, to run large data pipelines (reading raw files, computing volume backscatter, performing frequency differencing, etc.) with only a few lines of code. We will demonstrate how we used Echodataflow to process ship data from the U.S.-Canada Pacific Hake Acoustic Trawl Survey and discuss other use cases. We believe that this approach will increase the reproducibility and transparency of fisheries acoustics data pipelines and allow the community to learn from each other’s work. ","tags":["open-source","pipeline","fisheries acoustics","community engagement"],"title":"Scalable and configurable echosounder data workflows","type":"talk"},{"authors":["Dingrui Lei"],"categories":null,"content":"Echospace recruited contributor Dingrui Lei in 2023 to refactor an echosounder data interactive visualization package called echoshader.\n My 2023 Summer Internship with Echoshader: A Dive into Advanced Ocean Sonar Data Visualization Author: Dingrui Lei\nRef 1: Slides of presentation\nRef 2: Docs for this version\nHello, readers! I\u0026rsquo;m excited to share my summer internship experience working on the fascinating project, Echoshader. This Python package, designed to enhance the visualization of ocean sonar data, has been my focus this summer. While I won\u0026rsquo;t be delving into technical jargon, I\u0026rsquo;ll give you a glimpse of my journey, the challenges I faced, and the accomplishments achieved during my internship. The prototype was built during GSoC 2022.\nEchoshader: Bridging the Gap in Ocean Sonar Data Visualization Before I jump into the technical details, let\u0026rsquo;s take a moment to understand the significance of ocean sonar systems. These systems, including echosounders, are the unsung heroes of marine research. They help scientists study marine life by emitting sound waves and analyzing the echoes they bounce back. Think of it as an underwater ultrasound for the ocean. The data generated from these systems is invaluable for monitoring and conserving our marine ecosystems.\nEchoshader, our summer project, aims to make this data more accessible and interactive. It\u0026rsquo;s like a powerful toolset that enables scientists and researchers to visualize and analyze ocean sonar data effortlessly. But let\u0026rsquo;s get into the nitty-gritty of my experience.\nBuilding the Echoshader: A Structured Journey My summer project was all about creating and refining the Echoshader package. This package is the backbone of our mission, providing oceanographers and researchers with the tools they need to visualize and understand ocean sonar data. Here\u0026rsquo;s how I structured my work:\n1. The Echoshader Class: A Controller for Visualization At the heart of Echoshader lies the Echoshader class. This class is like the conductor of an orchestra, coordinating user interactions, data updates, and visualizations. My task was to make sure this class was robust and user-friendly.\nI defined the class and set up initial values and interactive widgets. These widgets allow users to tweak parameters and explore data interactively.\n2. Callbacks and Streams: Making It Interactive Echoshader needed to be interactive, allowing users to explore data dynamically. This required creating callback methods and stream objects. These elements connected user interactions to visualization updates, making the whole experience smooth and intuitive. 3. Extending Xarray with Accessors: A New Level of Functionality One of the exciting challenges I encountered was extending xarray\u0026rsquo;s functionality using accessors. This means adding custom methods and functionality to xarray objects, without cluttering the code with custom functions. We created a custom \u0026ldquo;eshader\u0026rdquo; accessor, which allowed us to take echogram visualization to the next level.\nA Glimpse into Echogram Visualization Echogram visualization is where the magic happens. It\u0026rsquo;s not just about pretty pictures; it\u0026rsquo;s about gaining insights into marine life and ecosystems.\n Echograms for Identifying Fish: Fisheries scientists rely on echograms to identify fish aggregations, scrolling through data collected on ships to assess populations. Echograms for Observing Zooplankton: Oceanographers use echograms to observe zooplankton movements in mooring data over extended periods. Tricolor Echograms: The \u0026ldquo;tricolor\u0026rdquo; echogram helps distinguish different fish species, thanks to its clever mapping of three frequencies to RGB colors.  Tracking and Curtain Visualization One of the most exciting aspects of Echoshader is tracking and curtain visualization. It\u0026rsquo;s like having a GPS for underwater data.\n Echogram-Control Mode: Visualizing data on a map helps assess fish associations with environmental variables. Track-Control Mode: Highlighting ship track sections on the map while viewing corresponding echograms offers precise insights into marine life at specific locations. Curtain Visualization: Representing longer data sections as curtains provides a broader spatial perspective on fish aggregations.   Histograms and Statistics Tables: Tools for Deeper Analysis Histograms and statistics tables are essential for fisheries scientists.\n Focused Analysis: Scientists can zoom in on specific data sections to examine volume backscattering strength (Sv) distribution and understand the types of fish present. Multi-Channel Comparisons: Comparing Sv distributions across multiple echosounder channels helps determine fish aggregation composition, offering valuable insights into the ecosystem.   In Conclusion: An Incredible Summer Journey My summer internship with Echoshader has been a remarkable journey. I\u0026rsquo;ve had the privilege of contributing to a project to advance oceanographic research and fisheries science. Echoshader isn\u0026rsquo;t just a package; it\u0026rsquo;s a gateway to uncovering the secrets of our oceans.\nIf you\u0026rsquo;re curious about ocean sonar data or want to explore the world of marine life, Echoshader is your partner in discovery. Feel free to reach out if you have questions or want to join us on this exciting journey. Until next time, happy exploring!\n","date":1695024e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1695024e3,"objectID":"53548d8621d0a8d3d259545c9fba93d4","permalink":"https://uw-echospace.github.io/2023/09/18/a-summer-of-refactoring-echoshader/","publishdate":"2023-09-18T00:00:00-08:00","relpermalink":"/2023/09/18/a-summer-of-refactoring-echoshader/","section":"post","summary":"Echospace hosted a contributor - Dingrui Lei, to refactor echoshader - a package for interactive visualization of echosounder data.","tags":null,"title":"A Summer of Refactoring Echoshader!","type":"post"},{"authors":["Aditya Krishna"],"categories":null,"content":"","date":1684503e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1684503e3,"objectID":"15898c73b1ad49b4fbbe54799879b45f","permalink":"https://uw-echospace.github.io/talk/202305-urp-symposium/","publishdate":"2023-05-19T15:30:00+02:00","relpermalink":"/talk/202305-urp-symposium/","section":"talk","summary":" ","tags":["bioacoustics","passive acoustic monitoring","machine learning"],"title":"Investigation of duty cycles in passive acoustic bat monitoring","type":"talk"},{"authors":["Dingrui Lei","Don Setiawan"],"categories":null,"content":"Echospace collaborates with the Integrated Ocean Observing Systems (IOOS) in the Google Summer of Code (GSoC) program in 2022 to jump start an echosounder data interactive visualization package called echoshader.\n Dingrui Lei is our great GSoC contributor, and our very own Don Setiawan is the primary mentor.\n My name is Dingrui Lei and I am a new graduate student at Rice University. My experience has given me a broader understanding of how computer science knowledge can solve engineering problems and facilitate new tech development. I’d like to utilize my computer science knowledge to solve engineering problems.\nBefore contacting the IOOS community, I read the article \u0026ldquo; Understanding Our Ocean with Water-Column Sonar Data,\u0026rdquo; and an introduction to the project echopype. Sonar is very intriguing to me, it can continuously detect the activities of sea creatures in the dimension of space and time. The depth of fish clusters changing with solar radiation really made me see the splendid usefulness of sonar data.\nOne of the main focuses of the Echospace team is sampling and interpretation of ocean acoustic data. Echopype sits in the middle, extracts raw data from the cloud or file server, converts them to netCDF or Zarr, and performs denoising and calibration. Another job is to interpret, where I give my effort to build a library called echoshader that can help oceanographers discover certain patterns from it. Echoshader, an open source project, aims to enhance the ability to interactively visualize large amounts of cloud-based data to accelerate the data exploration and discovery process. Ocean sonar data are generated from echopype, which handles the normalization, preprocessing and organization of echo data. Echoshader will be developed in parallel with the ongoing development of echopype.\nAs a participant of GSoC, I am developing the main APIs of echoshader based on the HoloViz suite of tools, test configuration for using echoshader widgets in Panel dashboards, and create Jupyter notebooks to demo use of the combination of tools.\nBefore starting coding, I read lots of documents to find the most suitable tool. Although there are many excellent and fantastic visualizing libraries with Python, such as plotly and bokh, they can not process xarray directly, which is a kind of multidimensional labeled data massively used in echopype. Then I locked my eyes on HoloViz ecosystem, whose tools and examples generally work with any Python standard data types (lists, dictionaries, etc.), plus Pandas or Dask DataFrames and NumPy, Xarray, or Dask arrays. After determining which type of tool to use, I began to read a user guide about HoloViz libraries. There are several libraries mainly used in echoshader: hvplot, Holoviews, GeoViews and Panel. Hvplot and HoloViews declare objects for instantly visualizable data, building Bokeh plots from convenient high-level specifications. GeoViews visualize geographic data corresponding to ship survey datasets. Panel assembles grams and control widgets from these different libraries into a layout which could be displayed in a Jupyter notebook and in a standalone servable dashboard. In addition to HoloViz libraries, PyVista and other libraries are involved for 3D extension, which also fit well in panel layout. Also, benchmarking and doc work are required for each module. Below are some screenshots of the different visualization functionalities I am developing:\nAlthough the project is not difficult, there are some other challenges I face. Learning Git and Github is a prerequisite for me to participate in open source projects for the first time. It is also my first time to collaborate with an English-speaking team. I had difficulty reading and writing English documents, not to mention, communicating. Fortunately, the mentors, Wu-jung, Don, Valentina, Brandon and Emilio are all kind and warmhearted, willing to give me suggestions and guidance.\nI really recommend future GSoC participants select the IOOS organization and echospace team as your target and exploit your ability and talent to contribute to the community. Water is extremely significant for holding an adequate food supply and a productive environment for all living organisms. So working here can not just improve your coding and teamwork capability, but also create a beautiful tomorrow for ourselves and our Mother Earth.\n","date":1658995200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1658995200,"objectID":"83f2d57e3e89c7219607596d3651954b","permalink":"https://uw-echospace.github.io/2022/07/28/hello-from-dingrui-lei-gsoc-contributor-of-echoshader/","publishdate":"2022-07-28T00:00:00-08:00","relpermalink":"/2022/07/28/hello-from-dingrui-lei-gsoc-contributor-of-echoshader/","section":"post","summary":"Echospace hosted a Google Summer of Code (GSoC) contributor to jump start [echoshader](https://github.com/OSOceanAcoustics/echoshader), a new package for interactive visualization of echosounder data.","tags":null,"title":"Hello from Dingrui Lei, GSoC contributor of Echoshader!","type":"post"},{"authors":["Wu-Jung Lee"],"categories":null,"content":"","date":1653315e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1653315e3,"objectID":"530ae95c04128df60979652f467f57db","permalink":"https://uw-echospace.github.io/talk/202205-asa-denver-keynote/","publishdate":"2020-10-10T08:28:33-08:00","relpermalink":"/talk/202205-asa-denver-keynote/","section":"talk","summary":"Keynote Lecture at the 2022 Denver Acoustical Society of America meeting.","tags":["open-source","fisheries acoustics","machine learning","echolocation","community engagement"],"title":"Understanding echoes","type":"talk"},{"authors":["Aditya Krishna"],"categories":null,"content":"","date":1653054300,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1653054300,"objectID":"4199f7b6fdb1d5d93349011a50d60317","permalink":"https://uw-echospace.github.io/talk/202205-urp-symposium/","publishdate":"2022-05-20T15:45:00+02:00","relpermalink":"/talk/202205-urp-symposium/","section":"talk","summary":" ","tags":["machine learning","bioacoustics"],"title":"Discerning behavioral habits of echolocating bats using acoustical and computational methods","type":"talk"},{"authors":["Wu-Jung Lee","Emilio Mayorga","Brandon Reyes","Don Setiawan","Imran Majeed","Valentina Staneva"],"categories":null,"content":"","date":1651075800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1651075800,"objectID":"3615a44a6bef7961a646d5fa47ad6612","permalink":"https://uw-echospace.github.io/talk/202204-wgfast-echopype/","publishdate":"2022-04-27T18:10:00+02:00","relpermalink":"/talk/202204-wgfast-echopype/","section":"talk","summary":"This presentation was also given at the NOAA National Centers for Environmental Information (NCEI) Water Column Sonar Data Archive 2022 Workshop on March 29, 2022.","tags":["open-source","fisheries acoustics","community engagement"],"title":"Updates from Echopype developers: changes and roadmap","type":"talk"},{"authors":["Valentina Staneva","Wu-Jung Lee"],"categories":null,"content":"","date":1650903e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1650903e3,"objectID":"a4d7fa4ba34ac13d5933cd0b52948459","permalink":"https://uw-echospace.github.io/talk/202204-wgfast-ooi-nmf/","publishdate":"2022-04-25T18:10:00+02:00","relpermalink":"/talk/202204-wgfast-ooi-nmf/","section":"talk","summary":" ","tags":["fisheries acoustics","machine learning"],"title":"Summarizing low-dimensional patterns in long-term echosounder time series from the U.S. Ocean Observatories Initiative network","type":"talk"},{"authors":["M Castellote","TA Mooney","R Andrews","S Deruiter","W-J Lee","M Ferguson","P Wade"],"categories":["echolocation"],"content":"","date":1638262800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1638262800,"objectID":"087c5247939077df40f97e3d76ba445c","permalink":"https://uw-echospace.github.io/publication/2021-castellote-etal-plosone-beluga-foraging-monitoring/","publishdate":"2020-11-30T08:30:00-08:00","relpermalink":"/publication/2021-castellote-etal-plosone-beluga-foraging-monitoring/","section":"publication","summary":" ","tags":[],"title":"Beluga whale (Delphinapterus leucas) acoustic foraging behavior and applications for long term monitoring","type":"publication"},{"authors":["Emilio Mayorga","Wu-Jung Lee"],"categories":null,"content":"","date":1635451200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1635451200,"objectID":"ef88e059c01e37136113b71da09801db","permalink":"https://uw-echospace.github.io/talk/202110-ioos-dmac/","publishdate":"2021-10-28T15:00:00-05:00","relpermalink":"/talk/202110-ioos-dmac/","section":"talk","summary":" ","tags":["open-source","fisheries acoustics","community engagement"],"title":"Scalable, interoperable processing of water column sonar data for biological applications using the echopype Python package","type":"talk"},{"authors":["Wu-Jung Lee"],"categories":null,"content":"","date":1633476600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1633476600,"objectID":"299baed0c00bb98ff9364204f8d23617","permalink":"https://uw-echospace.github.io/talk/202110-uw-data-sci/","publishdate":"2021-10-05T16:30:00-07:00","relpermalink":"/talk/202110-uw-data-sci/","section":"talk","summary":" ","tags":["machine learning","fisheries acoustics","community engagement"],"title":"Building a toolbox for studying marine ecology using large ocean sonar datasets","type":"talk"},{"authors":["**W-J Lee**","V Staneva"],"categories":["sonar","machine learning"],"content":"","date":1606726800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1606726800,"objectID":"4a4feb6c85adec03ad05fbb28f9f95b1","permalink":"https://uw-echospace.github.io/publication/2020-lee-staneva-jasa-tsnmf/","publishdate":"2020-11-30T08:30:00-08:00","relpermalink":"/publication/2020-lee-staneva-jasa-tsnmf/","section":"publication","summary":"We developd a data-driven methodology based on matrix decomposition to build compact representation of long-term echosounder time series using intrinsic features in the data.","tags":[],"title":"Compact representation of temporal processes in echosounder time series via matrix decomposition","type":"publication"},{"authors":["TK Stanton","**W-J Lee**","K Baik"],"categories":["sonar"],"content":"","date":1544086800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1544086800,"objectID":"a1e37933414666235979cbf1a7226373","permalink":"https://uw-echospace.github.io/publication/2018-stanton-etal-jasa-echo-stat-tutorial/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2018-stanton-etal-jasa-echo-stat-tutorial/","section":"publication","summary":"From basic foundational concepts to advanced topics in modeling the statistics of echoes from discrete scatterers, inspired by sonar observation of marine organisms.","tags":[],"title":"Echo statistics associated with discrete scatterers: A tutorial on physics-based methods","type":"publication"},{"authors":["**W-J Lee**","DJ Tang","TK Stanton","EI Thorsos"],"categories":["sonar"],"content":"","date":1537261200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1537261200,"objectID":"ad14b54c3e2ad726519a4ce474aac719","permalink":"https://uw-echospace.github.io/publication/2018-lee-etal-jasa-trex-fish/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2018-lee-etal-jasa-trex-fish/","section":"publication","summary":"Mid-frequency sonar provides a first-of-the-kind macroscopic observation of the nightly foraging runs of fish inhabiting a shallow-water artificial reef in northern Gulf of Mexico.","tags":[],"title":"Macroscopic observations of diel fish movements around a shallow water artificial reef using a mid-frequency horizontal-looking sonar","type":"publication"},{"authors":["**W-J Lee**","B Falk","C Chiu","A Krishnan","JA Arbour","CF Moss"],"categories":["echolocation"],"content":"","date":1513328400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1513328400,"objectID":"78cb62af20cb9718ce321d9e5351e66f","permalink":"https://uw-echospace.github.io/publication/2017-lee-etal-plosbio-rousettus-bp/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2017-lee-etal-plosbio-rousettus-bp/","section":"publication","summary":"Experimental measurements and theoretical modeling provided insights into the mechanisms by which tongue-clicking fruit bats change their echolocation sonar beam direction without changing head aim or mouth shape.","tags":[],"title":"Tongue-driven sonar beam steering by a lingual-echolocating fruit bat","type":"publication"},{"authors":null,"categories":null,"content":"\r[09/2025] Aditya and Wu-Jung published a paper in JASA on the effects of duty-cycling in PAM of bats!\n[07/2025] Wu-Jung and YeonJoon published two papers in JASA, on porpoise movements during target discrimination and dolphin head-related transfer function prediction!\n[05/2025] Multiple Echospace members hosted the second Bridge to Ocean Acoustics \u0026amp; Technology (BOAT) workshop in New Orleans!\n[03/2025] Multiple Echospace members will be hosting the first Bridge to Ocean Acoustics \u0026amp; Technology (BOAT) workshop in Seattle!\n[02/2025] Wu-Jung was awarded for the 2025 APL Science and Engineering Achievement Award! Congratulations!\n[02/2025] Caesar was accepted to the UW ECE PhD program and will start this fall, continuing his research in Echospace! Congratulations, Caesar!\n[10/2025] Ameena Majeed joined Echospace as an Undergrad Research Assistant. Welcome!\n[08/2025] Aidan Lee joined Echospace as an Undergrad Research Assistant. Welcome!\n[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.\n[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!\n[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.\n[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!\n[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.\n[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.\n[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.\n[12/2023] We welcome Dr. Brandyn Lucca to join Echospace as a SEED postdoctoral fellow!\n[12/2023] Soham gave a talk at 2023 PyData Global \u0026ndash; check out his abstract and the video recording!\n[10/2023] Valentina and Wu-Jung gave a talk and a poster presentation in the 2023 North Pacific Marine Science Organization (PICES) meeting in Seattle.\n[09/2023] YeonJoon was selected as a UW Data Science Postdoctoral Fellow.\n[09/2023] Wu-Jung joined the NOAA NCEI Water Column Sonar Data Archive stakeholder workshop and engaged in Echopype Q\u0026amp;As.\n[08/2023] Wu-Jung, Emilio, and Valentina hosted OceanHackWeek 2023 at UW with an international organizer team!\n[05/2023] Caesar Tuguinay joined the Echospace group as a Research Assistant. Welcome!\n[05/2023] We welcome Dingrui Lei and Soham Butala to join Echospace as summer interns!\n[06/2023] Valentina and Wu-Jung went to sea with the Hake survey on the NOAA FSV Bell M. Shimada!\n[05/2023] YeonJoon and Wu-Jung gave two talks on target discrimination behavior by a harbor porpoise and numerical modeling of sound transduction in dolphin head in the Chicago ASA meeting.\n[05/2023] Aditya presented his ongoing research on the effects of subsampling for passive acoustic monitoring of bats at UW\u0026rsquo;s 26th Annual Undergraduate Research Symposium.\n[03/2023] Valentina and Wu-Jung gave two talks on our software and machine learning developments at the 2023 ICES Fisheries and Plankton Acoustics Symposium in Portland, Maine, and together with Emilio engaged with the international fisheries acoustic community in data format discussions.\n[02/2023] Wu-Jung was invited to serve on the committee for Ocean Acoustics Education and Expertise of the National Academies, comissioned by ONR.\n[12/2022] Aditya has been awarded the Mary Gates Research Scholarship for his research on passive acoustic monitoring of bats in the Union Bay Natural Area!\n[08/2022] Many of us in Echospace and alumnus Derya are hosting the OceanHackWeek 2022 Northwest satellite this week!\n[07/2022] We welcome Dr. YeonJoon Cheong to join Echospace as a postdoc scholar!\n[05/2022] We have released a new, major version of echopype, 0.6.0. There are significant breaking changes, but also significant improvements in convention adherence, consistency across sensors, and dataset documentation.\n[05/2022] Wu-Jung will be giving the keynote lecture on \u0026ldquo;Understanding Echoes\u0026rdquo; in the ASA Denver meeting.\n[05/2022] Aditya gave a talk on using machine learning to monitor bats in UW\u0026rsquo;s 25th Annual Undergraduate Research Symposium.\n[04/2022] Wu-Jung and Emilio gave two talks on echopype updates and roadmap in the 2022 WGFAST meeting and the 2022 NOAA NCEI Water Column Sonar Data Archive workshop.\n[04/2022] Valentina gave a talk on analyzing OOI echosounder data using matrix decomposition in the 2022 WGFAST meeting.\n[11/2021] Valentina gave a tutorial at the Seattle ASA meeting on Software Best Practices\n[11/2021] New paper \u0026ldquo;Beluga whale (Delphinapterus leucas) acoustic foraging behavior and applications for long term monitoring\u0026rdquo; was published in PLOS One!\n[10/2021] New preprint \u0026ldquo;Echopype: A Python library for interoperable and scalable processing of water column sonar data for biological information\u0026rdquo; was posted on arXiv!\n[10/2021] Emilio and Wu-Jung gave the IOOS DMAC webinar on \u0026ldquo;Scalable, interoperable processing of water column sonar data for biological applications using the echopype Python package\u0026rdquo;.\n[10/2021] Wu-Jung gave the UW Data Science Seminar on \u0026ldquo;Building a toolbox for studying marine ecology using large ocean sonar datasets\u0026rdquo;.\n[09/2021] Wu-Jung and Linda successfully completed this summer\u0026rsquo;s fieldwork evaluating the use of an ADCP-equipped glider as a biological monitoring tool. Check out NOAA Exploration\u0026rsquo;s coverage of this mission!\n","date":1512086400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1512086400,"objectID":"a0812ae5f3c926fea6faf4472cefc8e2","permalink":"https://uw-echospace.github.io/news/","publishdate":"2017-12-01T00:00:00Z","relpermalink":"/news/","section":"","summary":"\r\nList of news.\r\n","tags":[],"title":"News","type":"page"},{"authors":["M Warnecke","**W-J Lee**","A Krishnan","CF Moss"],"categories":["echolocation"],"content":"","date":1456822800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1456822800,"objectID":"a6740d6f9c541530b0147e4b62950aee","permalink":"https://uw-echospace.github.io/publication/2016-warnecke-etal-frontier-echo-flow/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2016-warnecke-etal-frontier-echo-flow/","section":"publication","summary":" ","tags":[],"title":"Dynamic echo information guides flight in the big brown bat","type":"publication"},{"authors":["**W-J Lee**","TK Stanton"],"categories":["sonar"],"content":"","date":1448960400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1448960400,"objectID":"19f522a8e3a34d6d93e8a9702912fa78","permalink":"https://uw-echospace.github.io/publication/2015-lee-stanton-joe-broadband/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2015-lee-stanton-joe-broadband/","section":"publication","summary":" ","tags":[],"title":"Statistics of broadband echoes: application to acoustic estimates of numerical density of fish","type":"publication"},{"authors":["S Danilovich","A Krishnan","**W-J Lee**","I Borrisov","O Eitan","G Kosa","CF Moss","Y Yovel"],"categories":["echolocation"],"content":"","date":1435741200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1435741200,"objectID":"cf034d7a3031feb855711c7da7e6d2b9","permalink":"https://uw-echospace.github.io/publication/2015-danilovich-etal-currbio-rousettus-light/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2015-danilovich-etal-currbio-rousettus-light/","section":"publication","summary":" ","tags":[],"title":"Bats regulate biosonar based on the availability of visual information","type":"publication"},{"authors":["**W-J Lee**","CF Moss"],"categories":["echolocation"],"content":"","date":1430470800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1430470800,"objectID":"a25f6246a8c9f79b3362ad2cea9f4756","permalink":"https://uw-echospace.github.io/publication/2016-lee-moss-jasa-luna-moth/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2016-lee-moss-jasa-luna-moth/","section":"publication","summary":"The weak but persistent echoes from the hindwing tails of luna moths may help them confuse the sonar-guided bat predators, even though the tail echoes themselves are not strong enough to completely distract the bats' attention.","tags":[],"title":"Can the elongated hindwing tails of fluttering moths serve as false sonar targets to divert bat attacks?","type":"publication"},{"authors":["**W-J Lee**","TK Stanton"],"categories":["sonar"],"content":"","date":1389603600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1389603600,"objectID":"24263d6645cbfe8db02164b35dd1f972","permalink":"https://uw-echospace.github.io/publication/2014-lee-stanton-joe-mixed/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2014-lee-stanton-joe-mixed/","section":"publication","summary":" ","tags":[],"title":"Statistics of echoes from mixed assemblages of scatterers with different scattering amplitudes and numerical densities","type":"publication"},{"authors":["**W-J Lee**","AC Lavery","TK Stanton"],"categories":["sonar"],"content":"","date":1338541200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1338541200,"objectID":"c585813a61aa52ab35f4225934b7b0be","permalink":"https://uw-echospace.github.io/publication/2012-lee-etal-jasa-squid/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2012-lee-etal-jasa-squid/","section":"publication","summary":" ","tags":[],"title":"Orientation dependence of broadband acoustic backscattering from live squid","type":"publication"},{"authors":["TA Mooney","**W-J Lee**","RT Hanlon"],"categories":["sonar"],"content":"","date":1270112400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1270112400,"objectID":"89191ee7760dadd008639338d4b2bced","permalink":"https://uw-echospace.github.io/publication/2010-mooney-etal-squid-sedation/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2010-mooney-etal-squid-sedation/","section":"publication","summary":" ","tags":[],"title":"Long-duration anesthetization of squid (Doryteuthis pealeii)","type":"publication"},{"authors":["WWL Au","DS Houser","JJ Finneran","**W-J Lee**","LA Talmadge","PW Moore"],"categories":["echolocation"],"content":"","date":1267434e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1267434e3,"objectID":"dbe13c3b1a8c1af3b68032d14a6ff0f7","permalink":"https://uw-echospace.github.io/publication/2010-au-etal-jasa-tursiops-suctioncup/","publishdate":"2019-11-10T07:16:35-08:00","relpermalink":"/publication/2010-au-etal-jasa-tursiops-suctioncup/","section":"publication","summary":" ","tags":[],"title":"The acoustic field on the forehead of echolocating Atlantic bottlenose dolphins (Tursiops truncatus)","type":"publication"}]