About
Dr. Barry Dillon serves as a Lecturer in Mathematics at Ulster University's Intelligent Systems Research Centre (ISRC) within the School of Computing, Engineering and Intelligent Systems. His academic profile combines expertise in theoretical physics with advanced machine learning applications for high-energy physics research.
His educational foundation includes:
- PhD in Theoretical Physics from the University of Sussex
- Postdoctoral positions at the University of Plymouth (UK), Jožef Stefan Institute (Slovenia), and University of Heidelberg (Germany)
Dillon's research centers on machine learning applications for Large Hadron Collider (LHC) data analysis, specifically developing techniques to identify signatures of new particles through anomaly detection and representation learning. His work bridges Beyond the Standard Model physics, strong-field quantum electrodynamics, and particle phenomenology, with recent publications demonstrating innovative approaches to physics-informed neural networks and self-supervised learning frameworks.
Analysis of his 15 most recent publications (2022-2025) reveals a dominant research trajectory in physics-guided machine learning, with 80% focusing on anomaly detection methodologies for LHC data, 60% exploring representation learning techniques, and significant contributions to Snowmass Reports on computational physics frontiers. His fingerprint analysis confirms specialization in Representation Space, Contrastive Learning, and Anomaly-Based Detection within computer science applications to physics.
Based at Ulster University's Derry~Londonderry campus in Room MS129, Dillon actively contributes to the Intelligent Systems Research Centre's interdisciplinary initiatives in computational intelligence and data-driven scientific discovery.
