A5056491013- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Computational Physics and Python Applications
- Cosmology and Gravitation Theories
- Neutrino Physics Research
- Medical Imaging Techniques and Applications
- Agriculture and Rural Development Research
- Ecosystem dynamics and resilience
- Advanced Data Storage Technologies
- Ecology and Vegetation Dynamics Studies
- Distributed and Parallel Computing Systems
- Radiation Detection and Scintillator Technologies
- Parallel Computing and Optimization Techniques
- Medical Imaging and Analysis
- Advanced Neural Network Applications
- Spinal Fractures and Fixation Techniques
- Earth Systems and Cosmic Evolution
- Digital Radiography and Breast Imaging
- Radiation Dose and Imaging
- Electron and X-Ray Spectroscopy Techniques
- Atomic and Subatomic Physics Research
- Generative Adversarial Networks and Image Synthesis
University College London
2020-2025
A. Alikhanyan National Laboratory
2024
The London College
2022
The Alan Turing Institute
2020-2021
Patterning of vegetation in drylands is a consequence localized feedback mechanisms. Such feedbacks also determine ecosystem resilience-i.e. the ability to recover from perturbation. Hence, patterning has been hypothesized be an indicator resilience, that is, spots are less resilient than labyrinths. Previous studies have made this qualitative link and used models quantitatively explore it, but few analysed available data test hypothesis. Here we provide methods for monitoring resilience...
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by
Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented multiplicities expected at the High-Luminosity Large Hadron Collider (HL-LHC) pose significant challenges for track reconstruction, where traditional algorithms become computationally infeasible. To address this challenge, we present novel learned approach to reconstruction that adapts recent advances computer vision and object detection. Our architecture combines Transformer hit...
Barlow et al., (2020). pyveg: A Python package for analysing the time evolution of patterned vegetation using Google Earth Engine. Journal Open Source Software, 5(55), 2483, https://doi.org/10.21105/joss.02483
In high-energy particle collisions, secondary decays can be reconstructed as displaced vertices using the measured trajectories of charged particles. Such are useful in identifying and studying jets originating from $b$- or $c$-hadrons, which is a key component physics programs modern collider experiments. While machine learning has become mainstream physics, most applications on an per-object basis, for example prediction class labels regression object properties. However, vertex...