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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...
NSF HDR launches Year Two ML Challenge to build AI that works in the real world
The National Science Foundation’s Harnessing the Data Revolution (HDR) ecosystem launched its second Machine Learning (ML) Challenge, a community competition aimed at “scientific modeling out of distribution,”or teaching AI systems to hold up when conditions change across places, seasons or...
head and shoulder photo of Berger-Wolfe speaking in front of black background with image of computer chip graphic
Berger-Wolf named AAAI Fellow
Tanya Berger-Wolf, director of Ohio State’s Translational Data Analytics Institute and founding director of the NSF-funded Imageomics Institute, was elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). The honor recognizes significant, sustained contributions to...
A group of imageomics researchers at NeurIPS 2025 imageomics workshop
Imageomics at NeurIPS: From Pixels to Principles
Workshop, talks, and demos highlight interpretable vision, AI-ready data, and trait discovery for the tree of life
AI to the Rescue: How Artificial Intelligence is Helping Scientists Understand Biodiversity
Research collaboration with The Ohio State University published in Nature shows how AI is filling critical gaps in our knowledge of the natural world.

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 Launches New Catalog Showcasing Open Science Resources for AI and Nature
head and shoulder photo of Berger-Wolfe speaking in front of black background with image of computer chip graphic
Berger-Wolf named AAAI Fellow
Jenna Kline
Kline wins first place at ACM/IEEE SEC 2025 student research contest
Tanya Berger-Wolf
Berger-Wolf Featured on Now Ohio State Podcast
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