About
**Project Description**: This project develops a reproducible, hardware-aware MLOps pipeline for optimizing neural-network models for LHC hardware triggers. It combines automated architecture and quantization search, experiment tracking, physics-level validation, and FPGA deployment, with a reusable workflow demonstrated on an MHA-based minimum-bias anomaly-detection use case.
**Supervisor**: Ioannis Xiotidis
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The talk
Credits and licence
- Institution
- CERN
- Speaker
- Maksymilian Artur Moskwytyn
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed