11 citations · 19 across the 9 of their papers we have counts for
11 papers
Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training
Saúl Alonso-Monsalve, Fabio Cufino, Umut Kose +2
Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally dense, overlapping detector signatures.…
An ultrafast plenoptic-camera system for high-resolution 3D particle tracking in unsegmented scintillators
Till Dieminger, Saúl Alonso-Monsalve, Christoph Alt +7
Neutrino detectors, particle calorimeters and some dark matter detectors require dense and massive active materials. An extremely fine segmentation is desirable to achieve precise…
Submanifold Sparse Convolutional Networks for Automated 3D Segmentation of Kidneys and Kidney Tumours in Computed Tomography
Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano +1
Accurate delineation of kidney tumours in Computed Tomography (CT) is essential for downstream quantitative analysis and precision oncology, but manual segmentation is a specialise…
Prospects and Opportunities with an upgraded FASER Neutrino Detector during the HL-LHC era: Input to the EPPSU
FASER Collaboration, Roshan Mammen Abraham, Xiaocong Ai +115
The FASER experiment at CERN has opened a new window in collider neutrino physics by detecting TeV-energy neutrinos produced in the forward direction at the LHC. Building on this s…
Contrastive Learning for Robust Representations of Neutrino Data
Alex Wilkinson, Radi Radev, Saul Alonso-Monsalve
In neutrino physics, analyses often depend on large simulated datasets, making it essential for models to generalise effectively to real-world detector data. Contrastive learning,…
AI-based particle track identification in scintillating fibres read out with imaging sensors
Noemi Bührer, Saúl Alonso-Monsalve, Matthew Franks +2
This paper presents the development and application of an AI-based method for particle track identification using scintillating fibres read out with imaging sensors. We propose a v…