Machine Learning and AI in Nuclear Physics UK

Wednesday 27 Mar 2024, 12:00 → 16:00 Europe/London

MS016

Lee Barnby (University of Derby (GB)), Marc Herve Rene Labiche (STFC Daresbury Laboratory (GB))

Initial meeting discussing the use of AI and Machine Learning in nuclear phyiscs, including:

• in the analysis of experimental and simulated data
• the calibration and alignment of detectors
• performing theoretical calculations 

12:00 → 13:00 Arrival

Informal discussions. Room is will be open from 12 noon with hosts in attendance.

13:00 → 13:05 Welcome and Introduction

Speaker: Dr Marc Herve Rene Labiche (STFC Daresbury Laboratory (GB))

13:05 → 13:20 ML/AI implementations at CLAS12

Speaker: Dr Bryan McKinnon (University of Glasgow)

13:20 → 13:45 AI/ML and Nuclear Applications: Overview of Surrey projects

Speaker: Dr Caroline Shenton-Taylor (University of Surrey)

13:45 → 14:00 Machine Learning and Pulse Shape Analysis for Nuclear Instrumentation

Speaker: Dr Fraser Holloway

14:00 → 14:15 Machine learning for improvements to nuclear fusion diagnostics

Speaker: Kimberley Lennon (Sheffield Hallam University)

14:15 → 14:30 Enhancing phenomenological optical model optimisation with a feed-forward neural network

Speaker: Samuel Sullivan (University of Surrey)

14:30 → 14:45 Tea/coffee

The plans is that Lee will take orders and bring from the cafeteria.

14:45 → 15:00 Use of ML for unfolding jet properties

Speaker: Nicodemos Andreou (University of Derby (GB))

15:00 → 15:15 ML in ALICE and cross-experiment initiatives at CERN

Speaker: Lee Barnby (University of Derby (GB))

HEP Synergy.pdf

15:15 → 16:00 Discussion