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