IRIS-HEP Fellow: Nupur Oza
Fellowship dates: May – Aug, 2021
Home Institution: University of Pennsylvania
Project: Implementation of ML algorithms for ambiguity resolution in ACTS track reconstruction
The high-pileup of collisions associated with the upgrade of the HL-LHC will offer serious computational limitations to particle tracking. ACTS, an experiment independent tool for track reconstruction, is especially CPU-expensive in its ambiguity solving step. To mitigate this, this project seeks to implement ML-based algorithms for ambiguity solving and final track resolution within ACTS.More information: My project proposal
Mentors:
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Dr. Carlo Varni (UC Berkeley)
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Professor Heather Gray (UC Berkeley, LBNL)
- 8 Sep 2021 - "Deep Learning for Ambiguity Resolution in ACTS", Nupur Oza, IRIS-HEP Topical Meetings Recording: Deep Learning for Ambiguity Resolution in ACTS
Current Status
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