A5077639208- Particle physics theoretical and experimental studies
- Particle Detector Development and Performance
- Advanced Data Storage Technologies
- Computational Physics and Python Applications
- Distributed and Parallel Computing Systems
- High-Energy Particle Collisions Research
- Scientific Computing and Data Management
- Software System Performance and Reliability
- Software Engineering Research
University of Glasgow
2023-2025
Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, their fundamental connection to differential integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly efficiently in high-dimensional parameter spaces samples a highly non-trivial challenge – doubly so if resulting library remain usable by scientists as opposed...
Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, their fundamental connection to differential integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly efficiently in high-dimensional parameter spaces samples a highly non-trivial challenge – doubly so if resulting library remain usable by scientists as opposed...
To gain a comprehensive view of what the LHC tells us about physics beyond Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in general search-analyses are not statistically orthogonal, so performing combinations requires knowledge extent to which same events co-populate multiple analyses’ signal regions. We present novel, stochastic method determine this degree overlap, and graph algorithm efficiently find combination regions with no mutual...
Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, their fundamental connection to differential integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly efficiently in high-dimensional parameter spaces samples a highly non-trivial challenge -- doubly so if resulting library remain usable by scientists as opposed...
To gain a comprehensive view of what the LHC tells us about physics beyond Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in general, search are not statistically orthogonal, so performing combinations requires knowledge extent to which same events co-populate multiple analyses' signal regions. We present novel, stochastic method determine this degree overlap and graph algorithm efficiently find combination regions with no mutual optimises...