Overview: In part one of this two-part workshop, “Partnering to Advance AI Research & Development,” we begin with a broad focus on partnering opportunities available to advance AI research and development between the partnering institutions at University of Chicago, Fermilab, Argonne National Laboratory, and Toyota Technological Institute at Chicago (TTIC). This workshop will highlight and identify opportunities for synergistic R&D among our institutions. There will be multiple Q&A opportunities to provide as much interaction as possible.
Registration will close at close of business on November 2.
Cheryl Ingstad; Director, Artificial Intelligence & Technology Office, Department of Energy
Nick Feamster; Neubauer Professor, Department of Computer Science, and Director, Center for Data and Computing, University of Chicago
James Amundson; Head, Scientific Computing Division, Fermilab
Rick Stevens; Associate Laboratory Director for Computing, Environment and Life Sciences, Argonne National Laboratory
Cristina Thomas; Global R&D Services Leader and R&D Global Process Owner, 3M Global R&D Services
Who should attend: “Partnering to Advance AI Research & Development” will provide an opportunity to discuss interdisciplinary areas in AI for measurements in physical and biological sciences and engineering. We anticipate the workshop will resonate with researchers, graduate students, and technical managers working at the frontlines of AI with experience in data science, computing, and experimental sciences. Fruitful alliances will form during this workshop with which we can collectively harness large-scale funding opportunities at several federal research agencies.
Webinar participants will:
Next steps: There will be a technical workshop in Spring 2021 following this webinar. The full schedule is currently under development. Researchers from diverse domains such as data acquisition, metrology, cosmology, astronomy, particle physics, accelerator science, and chemistry will have the opportunity to focus on cutting-edge AI research and tools. Crucial areas such as inverse problems, uncertainty, active learning, and reinforcement learning will be explored more closely in the context of measurements.
Sponsors: This workshop is sponsored by the University of Chicago’s Office of Research and National Laboratories Joint Task Force Initiative’s “AI+Science“ grant and the Center for Data and Computing (CDAC) - an intellectual hub and incubator for data science and artificial intelligence research at the University of Chicago.
Acceptance of registration contingent upon review by Fermiab Foreign Visits and Assignments Office.
The Zoom connection information will be distributed via e-mail 24 hours in advance of the webinar. Attendees should block the event date and time on their calendar. Please ensure your Zoom name matches the name on your registration to ensure you're able to access the meeting. The Zoom connection link may not be shared.