Imageomics is an emerging interdisciplinary field at the crossroads of machine learning (ML), computer vision (CV), and biological sciences. It leverages visual data—from microscopic images of single-cell species to videos of megafauna—to extract and analyze biological information, specifically traits. By grounding ML models in existing scientific knowledge, Imageomics aims to make traits computable from images, facilitating insights into the evolution and function of living organisms. Imageomics poses research problems that resonate with the broad machine-learning community: multimodal representation learning, multi-sensor fusion, few-shot learning, imbalanced-class learning, video understanding, hierarchical classification, etc. When people leverage ML tools to solve biological questions, the foundational bridges between ML and biological sciences also provide opportunities to address key challenges in ML, creating a virtuous cycle between the two fields.
We welcome participation from anyone interested in learning about the field of Imageomics, including:
The workshop will feature keynote talks, paper presentations, and discussions on the latest research in Imageomics. We encourage participants to submit papers and demos related to the topics outlined in the Call For Papers. The workshop will also provide opportunities for networking and collaboration among researchers from diverse backgrounds.
To be updated.
