Farouk Mokhtar
University of California San Diego(US)
Publications by Year
Research Areas
Particle physics theoretical and experimental studies, High-Energy Particle Collisions Research, Quantum Chromodynamics and Particle Interactions, Particle Detector Development and Performance, Computational Physics and Python Applications
Most-Cited Works
- → Machine Learning for Particle Flow Reconstruction at CMS(2023)19 cited
- → FAIR AI models in high energy physics(2023)10 cited
- → Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors(2024)9 cited
- → Do graph neural networks learn traditional jet substructure?(2022)5 cited
- → Simulated datasets for detector and particle flow reconstruction: CLIC detector(2023)4 cited
- → Progress towards an improved particle flow algorithm at CMS with machine learning(2023)3 cited
- → Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance(2021)2 cited
- → Applications and Techniques for Fast Machine Learning in Science(2021)2 cited
- → Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders(2025)2 cited
- → Scalable neural network models and terascale datasets for particle-flow reconstruction(2023)2 cited