Introduction

I’m a machine-learning researcher specialising in computer vision, with a focus on applications in neutrino physics. I began my journey in 2018 and carried out my PhD research at CERN. Since 2021, I’ve been a member of the Rubbia group at ETH Zurich. My work primarily involves event reconstruction in neutrino experiments. I have contributed to DUNE in the United States and am currently involved in T2K and Hyper-K in Japan, as well as FASER at CERN. Within T2K, I serve as the convener for machine-learning activities for the near detector. I have presented my research at international conferences and published in respected journals, particularly on applying deep learning to neutrino analysis.

I also teach AI applications in neutrino physics and have previous teaching experience in Computer Architecture, Operating Systems Design, and Distributed Systems.

Neutrino event display

Experience

Selected publications

  • "Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training" Saúl Alonso-Monsalve, Fabio Cufino, Umut Kose, Anna Mascellani, André Rubbia, Nature Machine Intelligence, 2026.
    Journal arXiv Code
  • "An ultrafast plenoptic-camera system for high-resolution 3D particle tracking in unsegmented scintillators" Till Dieminger, Saúl Alonso-Monsalve, Christoph Alt, Claudio Bruschini, Noemi Bührer, Edoardo Charbon, Kodai Kaneyasu, Matthew Franks, Tim Weber, Davide Sgalaberna, Nature Communications, 2026.
    Journal arXiv
  • "Submanifold sparse convolutional networks for automated 3D segmentation of kidneys and kidney tumours in computed tomography" Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano, Lorena Escudero Sanchez, Scientific Reports, 2026.
    Journal arXiv Code
  • "Deep-learning-based low-energy trigger algorithms for the Hyper-Kamiokande experiment" Katharina Lachner, Saúl Alonso-Monsalve, Benjamin Richards, Davide Sgalaberna, Physical Review D, 2026.
    Journal arXiv Code
  • "Transformer-Based Pulse Shape Discrimination in HPGe Detectors with Masked Autoencoder Pre-training" Marta Babicz, Saúl Alonso-Monsalve, Alain Fauquex, Laura Baudis, Machine Learning Science and Technology, 2026.
    Journal arXiv
  • "Contrastive learning for robust representations of neutrino data" Alex Wilkinson, Radi Radev, Saúl Alonso-Monsalve, Physical Review D, 2025.
    Journal arXiv Code
  • "AI-based particle track identification in scintillating fibres read out with imaging sensors" Noemi Bührer, Saúl Alonso-Monsalve, Matthew Franks, Till Dieminger, Davide Sgalaberna, Journal of Instrumentation, 2025.
    Journal arXiv
  • "Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of simulated neutrino interactions" Saúl Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao, Adrien Molines, Clark McGrew, André Rubbia, Communications Physics, 2024.
    Journal arXiv Code
  • "Artificial intelligence for improved fitting of trajectories of elementary particles in dense materials immersed in a magnetic field" Saúl Alonso-Monsalve, Davide Sgalaberna, Xingyu Zhao, Clark McGrew, André Rubbia, Communications Physics, 2023.
    Journal arXiv Code
  • "Adversarial methods to reduce simulation bias in neutrino interaction event filtering at liquid argon time projection chambers" Marta Babicz, Saúl Alonso-Monsalve, Stephen Dolan, Kazuhiro Terao, Physical Review D, 2022.
    Journal arXiv
  • "Graph neural network for 3D classification of ambiguities and optical crosstalk in scintillator-based neutrino detectors" Saúl Alonso-Monsalve, Dana Douqa, César Jesús-Valls, Thorsten Lux, Sebastian Pina-Otey, Federico Sánchez, Davide Sgalaberna, Leigh H. Whitehead, Physical Review D, 2021.
    Journal arXiv
  • "Neutrino interaction classification with a convolutional neural network in the DUNE far detector" B. Abi et al. (DUNE Collaboration), Physical Review D, 2020.
    Journal arXiv
  • "Image-Based Model Parameter Optimization Using Model-Assisted Generative Adversarial Networks" Saúl Alonso-Monsalve, Leigh H. Whitehead, IEEE Transactions on Neural Networks and Learning Systems, 2020.
    Journal arXiv Code
  • "Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators" Saúl Alonso-Monsalve, Andrés Suárez-Cetrulo, Alejandro Cervantes, David Quintana, Expert Systems with Applications, 2020.
    Journal

For a comprehensive list of publications, please refer to the following profiles.

Google Scholar ResearchGate ORCID INSPIRE HEP

Invited talks

Public outreach talk at T3chFest (in Spanish)

Events organised

Highlighted awards and grants

  • ETH Zurich Spark Award 2026 (Top-five finalist) ETH Zurich: finalist with Till Dieminger and Davide Sgalaberna for the invention "A sharper eye for PET scanners".
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  • Swiss AI Initiative compute grant (Principal investigator) Swiss AI Initiative: 50,000 GPU hours on the Alps supercomputer for the project "Scalable and Transferable AI for Neutrino Physics", 2026.
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  • NERSC AI for Science award (Principal investigator) National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory: 5,000 Perlmutter GPU node-hours for the project "Deep Learning for Neutrino Event Reconstruction", 2025–2026.
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  • Swiss AI Initiative compute grant (Principal investigator) Swiss AI Initiative: 30,000 GPU hours on the Alps supercomputer for the project "Artificial Intelligence for Neutrino Physics", 2025.
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  • NSF HDR Machine Learning Challenge (Third place) Third place in the A3D3 Gravitational Wave Challenge, jointly with Marta Babicz, for detecting anomalous events in LIGO O3 data, 2025.
    Results
  • Enrique Fuentes Quintana Award Funcas: national award for the best doctoral thesis in Engineering, Mathematics, Physics and Architecture, Dec 2022.
    Details
  • SCIE–Fundación BBVA Young Computer Science Research Award Awarded for international research experience, industry collaborations, and contributions to deep learning, Nov 2022.
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  • Margarita Salas Research Award — Basic Sciences Madrid City Council: accésit for one of the best doctoral theses in Basic Sciences, Nov 2022.
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  • UC3M Outstanding Doctoral Thesis Award Doctoral Programme in Computer Science and Technology, 2020–2021 cohort; awarded Dec 2021.
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  • UC3M Social Council Excellence Award — Alumni Recognising excellent professional development within three to five years of graduation, Jun 2021.
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  • Spanish National Parallel Programming Competition Jornadas SARTECO: second place in Málaga (2017) and third place in Salamanca (2016), solving tasks with OpenMP, MPI, and CUDA.
    Results
  • T3chFest Programming Contest First place in the individual algorithmic-programming contest, using Python; UC3M, Madrid, Feb 2016.
    Results

Media & features

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