Partnering to Advance AI Research & Development Workshop

Partnering to Advance AI Research & Development

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.

Confirmed speakers:

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

Doug Elmore; Senior Research Specialist, 3M Corporate Research Analytical Laboratory

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:

• Hear from organizational leaders of each of the institutions and an industry leader about the broad initiatives and activities in AI research and development.
• Observe the strategic direction of AI research funding opportunities at the federal level
• Identify paths to increase the collaboration and coordination between the participating institutions in AI research.
• Be a part of the growing community of researchers in AI research across our institutions.

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.