FAIR for AI Workshop

US/Central
Argonne National Laboratory

Argonne National Laboratory

Description

Welcome to the FAIR for AI Workshop 2022 Workshop page! 

The primary focus of this project is to advance our understanding of the relationship between data and artificial intelligence (AI) models by exploring relationships among them through the development of FAIR (Findable, Accessible, Interoperable, and Reusable) frameworks. Using high-energy physics (HEP) as the science driver, this project will develop a FAIR framework to advance our understanding of AI, provide new insights to apply AI techniques, and provide an environment where novel approaches to AI can be explored.

There are two components to this workshop:

Registration
Registration for the FAIR4HEP Workshop
Participants
  • Avik Roy
  • Baixi Sun
  • Ben Blaiszik
  • Bhargav Madhusudan Joshi
  • Bogdan Nicolae
  • Buyun Liang
  • Caterina Doglioni
  • Christine Kirkpatrick
  • Christoph Kirst
  • Daniel Diaz
  • Daniel S. Katz
  • Dylan Sheldon Rankin
  • Eliu Huerta
  • Farouk Mokhtar
  • Geoffrey Fox
  • Grace Peng
  • Javier Mauricio Duarte
  • Joe Muse
  • Joeri Hermans
  • Josh Greaves
  • Ju Sun
  • Kati Lassila-Perini
  • Kibaek Kim
  • Kristofer Bouchard
  • Lukas Alexander Heinrich
  • Margaret Lentz
  • Mark Neubauer
  • Melissa Kathryn Quinnan
  • Murali Emani
  • Oliver Ruebel
  • Philip Coleman Harris
  • Ravi Madduri
  • Roger Rusack
  • ruike zhu
  • Sang Eon Park
  • Tobias Fitschen
  • Vlad Kindratenko
  • Tuesday, 7 June
    • 09:00 09:10
      Welcome 10m
      Speaker: Margaret Lentz (US Department of Energy)
    • 09:10 09:40
      PUNCH4NFDI 30m
      Speaker: Joeri Hermans (University of Liège)
    • 09:40 10:10
      FAIR on the European Open Science Cloud: the case of the Dark Matter Science Project in ESCAPE 30m
      Speakers: Caterina Doglioni (ESCAPE), Lukas Alexander Heinrich (ESCAPE)
    • 10:10 10:40
      CERN/CMS Open Data 30m
      Speaker: Kati Lassila-Perini (CERN)
    • 10:40 10:55
      Break 15m
    • 10:55 11:55
      Roundtable 1h
      Speakers: Daniel S. Katz (University of Illinois at Urbana-Champaign), Javier Mauricio Duarte (Univ. of California San Diego (US)), Kati Lassila-Perini (CERN), Kibaek Kim (Argonne (Bridge2AI)), Laura Biven (National Institutes of Health), Oliver Ruebel (Lawrence Berkeley National Laboratory)
    • 11:55 12:25
      Perspectives from NIH: FAIR Data and AI 30m
      Speaker: Laura Biven (National Institutes of Health)
    • 12:25 13:30
      Lunch 1h 5m
    • 13:30 14:00
      FAIR Simulation Surrogate Benchmarks and MLCommons 30m
      Speaker: Geoffrey Fox ( University of Virginia)
    • 14:00 14:30
      Advancing FAIR in the U.S. - Welcome to GO FAIR US 30m
      Speaker: Christine Kirkpatrick (San Diego Supercomputing Center)
    • 14:30 15:00
      ENDURABLE: Benchmark datasets for AI with queryable metadata 30m
      Speaker: Kristofer Bouchard (University of California at Berkeley and Lawerence Berkeley National Laboratory)
    • 15:00 15:15
      Break 15m
    • 15:15 15:45
      HPC-FAIR: A Framework Managing Data and AI Models for Analyzing and Optimizing Scientific Applications 30m
      Speaker: Murali Emani (Argonne National Laboratory)
    • 15:45 16:45
      Roundtable 1h
      Speakers: Ben Blaiszik (University of Chicago), Christine Kirkpatrick (San Diego Supercomputing Center), Cristoph Kirst (Lawrence Berkeley National Laboratory), Eliu Huerta (Argonne National Laboratory), Geoffrey Fox ( University of Virginia), Grace Peng (National Institutes of Health), Ravi Madduri (Argonne National Laboratory)