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Webinar: Wildlife Conservation Analytics using BisQue AI: A Collaborative Project with the Smithsonian Institution

Friday, May 5, 2023 | Virtual

10 am Pacific ♦ 11 am Mountain ♦ 12 noon Central ♦ 1 pm Eastern


Webinar materials

Presentation slides


About the webinar

BisQue is an open-source data storage and analysis web service developed by the Vision Research Lab (VRL) at UC Santa Barbara that offers a powerful platform for analyzing 4-dimensional image data. Bisque’s array of tools for image processing, analysis, and visualization makes it a versatile solution for a wide range of applications. Additionally, BisQue's unique architecture allows users to run any containerized AI module, making it a highly customizable and adaptable platform for data analysis.

This webinar will highlight a new collaborative project involving BisQue’s creators and researchers at the Smithsonian National Zoo and Conservation Biology Institute. Recognizing that BisQue is an ideal application for wildlife monitoring and conservation, Smithsonian researchers sought to deploy the BisQue services to help analyze aerial wildlife survey data in grasslands of North America and East Africa. The BisQue-Smithsonian collaboration is focused on developing cutting edge AI/Deep Learning solutions for quantitative aerial image/video analysis, in order to detect, track and monitor wildlife in remote areas. Researchers are using BisQue to manage large volumes of imaging data, annotate these data to train state-of-the-art AI models, and then use these models to automatically detect and locate animals to better understand the factors necessary for conservation of critical wildlife populations. Presenters will include Connor Levenson and Satish Kumar of UCSB-VRL/Center for Multimodal Big Data Science, and Lacey Hughey of The Smithsonian Institution. Join us to learn how AI-powered, computational scientific research technology is being harnessed for a more resilient and biodiverse planet.

What you'll learn

  • What BisQue is and some of its capabilities
  • How the project team integrates current AI models into BisQue
  • How the Smithsonian is using the results of the BisQueAI-trained models in their research and conservation efforts

The Presenters

Connor Levenson headshot
Connor Levenson
Research Engineer
Center for Multimodal Big Data Science
Lacey Hughey, headshot
Lacey Hughey Ecologist/Program Manager
Smithsonian Conservation Biology Institute
Satish Kumar, headshot
Satish Kumar 
Graduate Student Researcher
Center for Multimodal Big Data Science


Project Principal Investigator

B.S. Manjunath, Director, Center for Multimodal Big Data Science and Healthcare, Dept. of Electrical and Computer Engineering, University of California, Santa Barbara