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Workshop on Applying Advanced AI Workflows in Astronomy and Microscopy


Register to Attend

This one-day workshop will focus on the challenges shared between observational astronomy and modern microscopy workflows. Advances in instrumentation, computation and data management for both microscopy and astronomy suggest opportunities for the broader scientific community to learn from the challenges common to both fields. The high-velocity, high-volume data generated by endeavors such as the Large Synoptic Survey Telescope (LSST) or the Square Kilometer Array (SKA) will require new techniques and cyberinfrastructure such as that provided by the Pacific Research Platform to handle the data they will produce. Best practices developed in these contexts may be applied to other domains.

We will introduce some of the challenges in microscopy and provide a survey of the techniques available to astronomers to deal with the ever-increasing flow of data, such as adopting streaming workflows (versus file-based workflows), Artificial Intelligence and Machine Learning, and GPU-accelerated analysis, as well as storage and data distribution, approaches that scale to the needs of a global community of researchers engaged in advanced microscopy imaging.

Please register by September 4 for this free event.

Proposed Summit Agenda

9:00 am- 10:00 am Registration 

10:00 am -11:00 am Keynote

11:00 am – 12:00 pm Challenges of Advanced Microscopy Workflows (20 min each)

12:00 – 1:00 pm Lunch Roundtables 

1:00 – 2:00 pm AI in Astronomy (20 Min. each)

2:00 – 3:00 pm Advanced CI Engineering (20 Min. each)

3:00 – 3:15 pm Closing Remark 

3:30 pm Adjourn

“It turns out that the challenges of peering into the universe are similar to those associated with peering into a microscope.”

-Larry Smarr, Principal Investigator of the Pacific Research Platform, Director, Qualcomm Institute.

Funding provided by CITRIS and the Banatao Institute, UC Santa Cruz and UC Merced, in collaboration with the Pacific Research Platform. Funding provided by the National Science Foundation, award #ACI-1541349.