SAINTS Short Course: AI and ML Applications in Nuclear and Particle Physics (SC-AINPP)

1. Nkadimeng E Dr., PhD , iThemba LABS
2. Manaka T Ms., MSc, Witwatersrand University
3. Mathaha T Mr., MSc ,  Witwatersrand University
4. Mosomane C Dr., PhD ,  iThemba LABS

Module 1: Fundamentals of AI/ML in Scientific Research

This module introduces the core concepts of AI and ML, tailored for applications in nuclear and particle physics. Participants will explore the impact of AI/ML on scientific research, understand basic algorithms, and discuss the ethical considerations inherent in deploying AI technologies in research.

Key Topics:

• • Introduction to AI and ML: Definitions and Distinctions - 1 hour
  • Overview of AI/ML Applications in Nuclear and Particle Physics - 1 hour
  • Ethical Implications of AI in Scientific Research

Module 2: AI/ML in Nuclear Physics

Focused on nuclear physics, this module examines the application of AI and ML for data analysis, predictive modeling, and optimization of experimental setups. Real-world case studies will be presented to illustrate the transformative potential of AI/ML in nuclear research.

Key Topics:

• • Predictive Modelling and Data Analysis in Nuclear Physics
  • AI Techniques for Optimizing Nuclear Experiments

Module 3: AI/ML in Particle Physics and Integration Techniques

Turning to particle physics, this module addresses the use of AI and ML for event reconstruction, particle identification, and simulation. The session will also cover strategies for integrating AI/ML into existing research workflows, with an emphasis on interdisciplinary collaboration and ethical AI use.

Key Topics:

• • AI/ML for Event Reconstruction and Particle Identification
  • Integrating AI/ML into Particle Physics Research Workflows
  • Ethical Considerations and Collaborative AI Research in Particle Physics

Hands-on Training:
Each day concludes with a hands-on training session, providing participants with practical experience in applying AI/ML techniques to data sets from nuclear and particle physics experiments. These sessions are designed to reinforce the day's learning and give attendees the confidence to apply AI/ML in their own research.

Final Assessment and Presentations:
On the final day, participants will have the opportunity to present their projects, developed during the hands-on sessions, to their peers and facilitators. This will include a discussion of the AI/ML techniques applied, insights gained, and potential impact on their research areas.

Target Audience: Postgraduate students (Honors, Masters, PhD) and junior research staff in nuclear and particle physics.

By completing this course, participants will be equipped with a fundamental understanding of how AI and ML technologies can be harnessed to drive innovation and efficiency in nuclear and particle physics research, poised to contribute to the advancement of these critical scientific domains.