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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
  • Victoria Dominguez Del Angel
  • Vlad Kindratenko
  • Tuesday 7 June
    • 1
      Welcome
      Speaker: Margaret Lentz (US Department of Energy)
    • 2
      PUNCH4NFDI
      Speaker: Joeri Hermans (University of Liège)
    • 3
      FAIR on the European Open Science Cloud: the case of the Dark Matter Science Project in ESCAPE
      Speakers: Caterina Doglioni (ESCAPE), Lukas Alexander Heinrich (ESCAPE)
    • 4
      CERN/CMS Open Data
      Speaker: Kati Lassila-Perini (CERN)
    • 10:40
      Break
    • 5
      Roundtable
      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)
    • 6
      Perspectives from NIH: FAIR Data and AI
      Speaker: Laura Biven (National Institutes of Health)
    • 12:25
      Lunch
    • 7
      FAIR Simulation Surrogate Benchmarks and MLCommons
      Speaker: Geoffrey Fox ( University of Virginia)
    • 8
      Advancing FAIR in the U.S. - Welcome to GO FAIR US
      Speaker: Christine Kirkpatrick (San Diego Supercomputing Center)
    • 9
      ENDURABLE: Benchmark datasets for AI with queryable metadata
      Speaker: Kristofer Bouchard (University of California at Berkeley and Lawerence Berkeley National Laboratory)
    • 15:00
      Break
    • 10
      HPC-FAIR: A Framework Managing Data and AI Models for Analyzing and Optimizing Scientific Applications
      Speaker: Murali Emani (Argonne National Laboratory)
    • 11
      Roundtable
      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)