AI for Experiments - Research Collaboration (JTFI Workshop, Part II) In Person

Alvin Tollestrup Auditorium (IARC)

Alvin Tollestrup Auditorium


Fermilab Batavia, IL
Eric Jonas (U of Chicago), Jayakar (Charles) Thangaraj (Fermilab), Mauricio Suarez (Fermilab), Nhan Tran (Fermilab), Paul Fenter (Argonne), Yuxin Chen (U of Chicago)

Registration is Now Open! (by invitation only)

AI for Experiments -Research Collaborations (JTFI Workshop-Part II)

­­The organizing committee invites you to the “AI for experiments – research collaborations” workshop to be held on Thursday October 20th, 2022.  The workshop hosted by Fermi National Accelerator Laboratory, University of Chicago, and Argonne National Laboratory will be at Fermilab focusing on opportunities to collaborate on AI research between the three institutions. The in-person sessions are reserved for invitation-only participants, and we look forward to your in-person attendance. We expect around 30 participants in total from the three institutions who are interested in collaborating and pushing the frontier in AI crucial areas such as inverse problems, uncertainty, active learning, and reinforcement learning in the context of measurements. Your participation, therefore, is vital to the success of this workshop. Refreshments and lunch will be provided for in-person participants.

Kindly note, the morning presentations will be broadcasted for virtual participants, while an interactive virtual session will be made available in the evening for questions, brainstorming, and discussions around the workshop topics (see agenda). As a reminder, this event is part two of the two-part “AI + measurements” JTFI workshop, which aims to forge new connections and collaborations between the organizing institutions. See a description of the first workshop here.

There will be multiple breakout sessions to provide as much interaction as possible. Please come with your topics where all three institutions can collaborate.

Deadline to register: September 30th at 6:00 PM CDT.

Complete step 1 to register and step 2 to request onsite access.

Who should attend? “AI for experiments – research collaborations” will provide an opportunity to discuss interdisciplinary areas in AI for experiments in sciences and engineering. For the in-person session, targeted attendees are researchers working at the frontlines of AI or experimentalists with AI-relevant problems. For the virtual session, researchers, post-docs, and graduate students interested in AI for experiments are welcome to attend. A separate Indico page will be set for the virtual session.

Objective: to forge new connections between Fermilab, University of Chicago, Toyota Technological Institute at Chicago (TTIC), and Argonne on the topics of intersection of AI and experimental measurements. Researchers from diverse domains such as data acquisition, metrology, cosmology, astronomy, particle physics, accelerator science, and chemistry are encouraged to participate and gain exposure to cutting-edge AI research and tools.

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.

  • Aashutosh Mistry
  • Adam Lyon
  • Adarsha Balaji
  • Aleksandra Ciprijanovic
  • Anna Szabo
  • Ashwin Samudre
  • Benjamin Hawks
  • Chibueze Amanchukwu
  • Claire Donnat
  • Eamon Duede
  • Eric Jonas
  • Farah Fahim
  • Gabriel Perdue
  • Giuseppe Cerati
  • J. Charles Thangaraj
  • James Amundson
  • Jason St. John
  • Jennifer Ngadiuba
  • Jim Kowalkowski
  • Joshua Isaacson
  • Julia Lane
  • Kevin Pedro
  • Kyle Hazelwood
  • Lu Zhang
  • Mathew Cherukara
  • Mauricio Suarez
  • Nhan Tran
  • Paul Fenter
  • Rebecca Willett
  • Rina Barber
  • Ross Harder
  • Sam McDermott
  • Sandeep Madireddy
  • Stephan Hruszkewycz
  • Subramanian Sankaranarayanan
  • Tammy Gloss
  • Tingjun Yang
  • Walter Hopkins
  • Yuxin Chen
Event Organizer: Mauricio Suarez
    • Welcome: Arrival
    • Welcome
      Conveners: Bonnie Fleming (Fermilab), Mauricio Suarez (Fermilab)
    • Presentation: How Can ML Advance Scientific Measurement?
      Convener: Eric Jonas (University of Chicago)
    • Presentation: HPI + AI-Enabled X-ray Science at the Advanced Photon Source
      Convener: Mathew Cherukara (Argonne)
    • 10:00 AM
    • Presentation: Efficient Machine Learning in HEP
      Convener: Jennifer Ngadiuba (Fermilab)
    • Presentation: Quantifying Predictive Uncertainty with Conformal Inference
      Convener: Rina Barber (University of Chicago)
    • Break-Out Rooms: Open Discussion & Participation
      Convener: Yuxin Chen (University of Chicago)
    • Lunch
    • Break-Out Rooms: 1st Round
      Conveners: Eric Jonas (U of Chicago), Nhan Tran (FNAL), Paul Fenter (Argonne), Yuxin Chen (U of Chicago)
    • 1:45 PM
    • Break-Out Rooms: 2nd Round
      Conveners: Eric Jonas (U of Chicago), Nhan Tran (FNAL), Paul Fenter (Argonne), Yuxin Chen (U of Chicago)
    • 2:45 PM
    • Panel: Questions & Panel Discussion
      Conveners: Eric Jonas (U of Chicago), Nhan Tran (FNAL), Paul Fenter (Argonne), Yuxin Chen (University of Chicago)
    • Closing
      Convener: James Amundson (Fermilab)