Organizers: Cris Fanelli (William & Mary/JLab), Diana McSpadden (JLab/Data Science), Kishan Rajput (JLab/Data Science)
Advisory and problem definition: Evaristo Cisbani (INFN), Wouter Deconinck (U. Manitoba)
Computing resources: Eric Walter (William & Mary, IT)
Data generation, Documentation, Validation: James Giroux (U. Regina), Karthik Suresh (U. Regina)
Technical Assistance: Eric Walter (William & Mary, IT), James Giroux (U. Regina), Karthik Suresh (U. Regina)
More info: a monetary prize for the winning solution will be provided. Winners are offered the possibility to give a talk at the next AI4EIC workshop (held annually). A non-cash prize (and the possibility of a talk at the next AI4EIC workshop) is also anticipated for the most innovative solution in case it will not coincide with the winning solution.
List of teams (please form your team if you want AWS resources! Contact ai4eichackathon@gmail.com):
https://docs.google.com/spreadsheets/d/1UzTGyMYiT1I0SKEJrd1gHorz4kHITEIDk0oK53V6PeU/edit#gid=1691241232
Leaderboard: https://ai4eichackathon.pythonanywhere.com/leaderboard
PDF Documentation: link here
Zenodo link (dataset and documentation): https://doi.org/10.5281/zenodo.7197023
October 14, 8:45 am to 5pm ET (hybrid: in-presence and virtual)
In-presence:
William & Mary, Raymond A. Mason School of Business, Alan B. Miller Hall
room 1019
101 Ukrop Way, Williamsburg, VA 23185
Remote:
Zoom coordinates:
https://jlab-org.zoomgov.com/j/1614875218?pwd=RFRPcGlNM3BaS0pQaDhxS3JURkdJZz09
Meeting ID: 1614875218
Password: 925723
