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| Description | Speaker: Julia Gonski Title: AI/ML Across the Data Pipeline: Designing 'New' New Physics Searches at the Energy Frontier Abstract: The coincidence of rapid technological developments in both machine learning (ML) and microelectronics have opened the door to increased intelligence in modern physics experiments, from the “edge” at-source to offline analysis. Such capability is driven by the need for new fundamental physics and can be naturally incorporated into the data pipelines of energy frontier collider experiments. In this talk I will describe novel applications of ML to collider data acquisition and analysis, starting with searches for beyond the Standard Model physics, trigger applications, and finally to processing on the detector. The future of this work is discussed in the context of planning for next-generation international collider facilities and the long-term outlook for discovery. Zoom: https://ucdavis.zoom.us/j/92176400190?pwd=cHhWZ1FGUHJWVUJrMTA5RGNRZDJudz09 |
| Location | PHY 285 |
| Date | Tue, November 12, 2024 |
| Time | 4:00pm-5:00pm PST |
| Duration | 1 hour |
| Access | Public |
| Created by | High-Energy Seminars |
| Updated | Sun, November 10, 2024 12:32pm PST |
| Send Reminder | Yes - 20241110 |
