Computer Vision for Drug Discovery: Where are we and What is Beyond?

Though start and end times here are correct, detailed schedules here may not be complete or up to date. Please be sure to cross reference the workshop's website to verify workshop schedule details if they are available on the workshop's website. (Added by CVPR.)

The workshop aims to bridge the gap between computer vision, artificial intelligence, and the life sciences, with a focus on transformative advancements in drug discovery. By integrating innovative imaging modalities—such as Spatial Transcriptomics, Cell Painting, and Optical Pooled Screening—with state-of-the-art computer vision techniques, this workshop seeks to foster collaboration between experts in biomedical science, AI, and computer vision.x000D
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The workshop highlights the potential for revolutionizing drug discovery processes, driving faster and more accurate identification of therapeutic targets, and expediting the development of treatments for complex diseases. Addressing pressing challenges like cancer, neurodegenerative disorders, and pandemics, the focus lies on leveraging AI to analyze high-dimensional biological data, enhancing our understanding of disease mechanisms and responses to therapies.x000D
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For the CVPR community, this represents an exciting opportunity to expand beyond traditional image processing tasks into applications with tangible societal impact. By applying computer vision expertise to critical healthcare and pharmaceutical challenges, participants will engage with tasks like multi-modal data fusion, enhancing explainability in biomedical applications, and addressing the unique complexities of biological imaging, such as sparse or noisy datasets.x000D
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This workshop is aligned with CVPR’s growing emphasis on “AI for social good,” offering computer vision researchers a platform to contribute to advances in medical science that could improve the lives of millions. It is a call to action for interdisciplinary innovation, uniting diverse expertise to tackle some of the most critical challenges in global health.