ePIC AI Town Hall Meeting
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US/Eastern
Markus Diefenthaler
(Jefferson Lab),
Sylvester Joosten
(Argonne National Laboratory),
Torre Wenaus
(BNL),
Wouter Deconinck
(University of Manitoba)
Description
The AI Town Hall Meeting aims to achieve two important goals:
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We would like to give anyone in the collaboration an opportunity to showcase the AI/ML projects they are working on. If you would like to present, please reach out to us directly, and we will add you to the agenda. Your presentation will enrich the discussions and inspire the work on AI/ML in ePIC.
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This town hall meeting also provides a chance for everyone in the collaboration to gain insight into the various AI/ML activities happening within ePIC.
We will use Zoom for the remote meeting:
- https://jlab-org.zoomgov.com/j/1614875218?pwd=RFRPcGlNM3BaS0pQaDhxS3JURkdJZz09
- Meeting ID: 1614875218
- Password: 925723
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AI/ML Workflow for BHCal CalibrationSpeaker: Derek Anderson (Iowa State University)
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ML4FPGA for Data ReductionSpeaker: Dmitry Romanov (Jefferson lab)
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ePIC dRICH Detector Using Deep LearningSpeaker: Omar Hassan (University of Victoria)
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Scattered Electron Reconstruction in the Low-Q2 TaggerSpeaker: Simon Gardner (University of Glasgow)
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ML Particle Identification With 3d Shower Profiles From CalorimetrySpeaker: Chao Peng (Argonne National Laboratory)
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AI/ML for Roman Pot MeasurementsSpeaker: David Ruth (alum@unh.edu;employee@unh.edu;faculty@unh.edu;member@unh.edu)
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Domain Adaptation In Lambda Tagging With Domain Adversarial GNNs And Normalizing FlowsSpeaker: Matthew McEneaney (staff@duke.edu;student@duke.edu;member@duke.edu)
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AI4EIC: Collaborations with Data Science CommunitySpeaker: Cristiano Fanelli (W&M)