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Imageomics Publication Awarded the Robert May Prize
Imageomics researcher, Jenna Kline, has been awarded for a major international ecology award for her work on new methods to study animal behavior using advanced technology. The Robert May Prize is a prestigious international recognition reserved for early-career researchers who deliver the year's...
Imageomics Launches New Catalog Showcasing Open Science Resources for AI and Nature
If last week’s Cyber Specials slipped past you, there’s good news - Imageomics just rolled out something even better. The Imageomics Catalog is now live, bringing together an impressive collection of public code, datasets, models, and spaces, all in one easy-to-explore hub. Designed to accelerate...

Images as the source of information about life

Biologists must analyze traits in order to understand the significance of patterns in the two billion-year evolutionary history of life and to predict future effects of environmental change or genetic manipulation. Images are by far the most abundant source of documentation of life on the planet—but traits of organisms cannot be readily extracted from them.

The question: How do we take hundreds of thousands of images and use them to answer fundamental biological questions about ecology and evolution? At the very least, how do we extract traits, such as the example of a bird guide?

The answer: We make traits computable. Biology meets machine learning and vice versa.

Introducing imageomics (NSF OAC-2118240)

Guide guide.imageomics.org Guides to Imageomics workflows, documentation, and general best-practices for collaborative science
Catalog catalog.imageomics.org All Imageomics code, data, models, and demos hosted on GitHub or Hugging Face are searchable through the Imageomics Catalog.
News
Imageomics Digital Digest, Issue 9
Inside the First Imageomics Conference
Imageomics Publication Awarded the Robert May Prize
Imageomics Digital Digest, Issue 8
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Events
FloraPalooza 2026
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Experiential Introduction to AI and Ecology Course - Part 1
Experiential Introduction to AI and Ecology Course - Part 2: Field Course
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