Imageomics: Images as the Source of Information about Life

‍Abstract

Introducing the new field of imageomics: from images to biological traits using biology-structured machine learning.

Images are the most abundant, readily available source for documenting life on the planet. Coming from natural history collections, laboratory scans, field studies, camera traps, wildlife surveys, autonomous vehicles on the land, water, and in the air, as well as tourists’ cameras, citizen scientists’ platforms, and posts on social media, there are millions of images of living organisms. But their power is yet to be harnessed for science and conservation. Even the traits of organisms cannot be readily extracted from images. The analysis of traits, the integrated products of genes and environment, is critical for biologists to predict effects of environmental change or genetic manipulation and to understand the significance of patterns in the four billion year evolutionary history of life.

Knowledge-guided machine learning and computer vision can turn massive collections of images into high resolution information database about living organisms, enabling scientific discovery, conservation, and policy decisions. This is our vision of the new scientific field of imageomics.

Biography

Dr. Tanya Berger-Wolf is a Professor of Computer Science Engineering, Electrical and Computer Engineering, and Evolution, Ecology, and Organismal Biology at the Ohio State University, where she is also the Director of the Translational Data Analytics Institute. As a computational ecologist, her research is at the unique intersection of computer science, AI, wildlife biology, and social sciences.

Berger-Wolf is a member of the US National Academies Board on Life Sciences, Advisory Committee for the Global Partnership on AI (GPAI) AI on Biodiversity working group, and CNRS International Scientific Advisory Board for AI for Science, Science for AI (AISSA) Centre, among many others. Berger-Wolf has received numerous awards for her research and mentoring, including University of Illinois Scholar, UIC Distinguished Researcher of the Year, US National Science Foundation CAREER, Association for Women in Science Chicago Innovator, and the UIC Mentor of the Year.

Berger-Wolf is also a director and co-founder of the AI for conservation non-profit Wild Me, home of the Wildbook project. Wildbook has been recently chosen by UNSECO as one of the top AI 100 projects worldwide supporting the UN Sustainable Development Goals.  Berger-Wolf has given hundreds of talks about her work, including at TED/TEDx and UN/UNESCO AI for the Planet.