Workshop for Large-Scale Scientific Imaging

Description

Join this two-day workshop on "Large-Scale Scientific Imaging" in celebration of the inception of the Scientific Software Engineering Center (SSEC) at Johns Hopkins, operating as part of the broad AI-X effort and funded by Schmidt Futures.

The area of large-scale scientific imaging forms one of the pillars of the emerging artificial intelligence (AI) revolution in science, as the explosion of scientific data is mostly due to the advancement of imaging technologies. This is true for nearly every scientific discipline, including medicine (radiology, brain and cancer research, etc.) astronomy, climate observations, materials science, cell biology, and more. And large-scale numerical simulations create ultra-high-resolution images of observable phenomena from turbulence to climate models and ocean circulation patterns.

What has not advanced similarly is the handling of these datasets, most of which are well past the Terabyte scale; even mid-scale instruments can generate several petabytes per year. Researchers have tackled data management mostly in a one-off fashion, specific to each experiment. This has created the potential for some of the most efficient and valuable techniques developed thus far to stay siloed and inaccessible from the broader scientific community.

This workshop brings together different communities to address these outstanding problems. Through speakers and facilitated discussion, participants will explore commonalities, identify differences, and see how to use better economies of scale in creating and managing such large image archives. Furthermore, participants will discuss ways to interface these image archives to existing AI environments and shorten the path to create novel AI applications for training and inference.

The first day will be dedicated to approximately 15-minute presentations by invited scientists from Johns Hopkins and beyond. The second day will be devoted to discussion sessions looking for synergies and common patterns between these different fields.

All in-person events at Johns Hopkins must follow university COVID-19 policies. See current guidelines online.