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.
Experience
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2021Feb – now
Senior scientist
ETH Zürich, Zurich, Switzerland -
2018–2021Feb – Jan
Doctoral student
CERN, Geneva, Switzerland -
2019Mar – Apr
Visiting student
University of Cambridge, Cambridge, United Kingdom -
2017Jul – Sep
CERN openlab summer student
CERN, Geneva, Switzerland -
2015–2018Jul – Jan
Research and teaching assistant
Universidad Carlos III de Madrid, Madrid, Spain
Selected publications
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"Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators" , Andrés Suárez-Cetrulo, Alejandro Cervantes, David Quintana, Expert Systems with Applications.
For a comprehensive list of publications, please refer to the following profiles.
Invited talks
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"From pixels to particles: deep learning in accelerator neutrino experiments" ( CAMBRIDGE, UNITED STATES) Plenary talk, 2026 IAIFI Summer Workshop, MIT.
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"Deep learning for neutrino physics" ( LONDON, UNITED KINGDOM) Plenary talk, NuPhys 2026: Prospects in Neutrino Physics, King's College London.Slides
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"Algorithmic View on Deep Learning for Accelerator Neutrino Experiments" ( ZURICH, SWITZERLAND) Plenary talk, ZPW2026: Machine Learning Techniques for Particle Physics, University of Zurich.Slides
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"Pushing the boundaries of neutrino physics with deep learning" ( MENLO PARK, UNITED STATES) Seminar, SLAC FPD Seminar, SLAC National Accelerator Laboratory.Slides
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"Machine learning methods for event reconstruction in accelerator neutrino experiments" ( L’ÉPINE, FRANCE) Conference talk, 5th World Summit on Exploring the Dark Side of the Universe (EDSU2024), Île de Noirmoutier.Slides
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"Artificial intelligence and machine learning in neutrino physics" ( PROCIDA, ITALY) Conference talk, 22nd International Workshop on Next Generation Nucleon Decay and Neutrino Detectors (NNN23), Procida.Slides
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"Computer vision introduction" ( MENLO PARK, UNITED STATES) Lecture, 51st SLAC Summer Institute (SSI 2023), SLAC National Accelerator Laboratory.
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"Machine learning for neutrino experiments" ( KASHIWA, JAPAN) Seminar, Kavli Institute for the Physics and Mathematics of the Universe (IPMU), University of Tokyo.Talk
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"Machine learning and high-performance computing for neutrino oscillations" ( NICOSIA, CYPRUS) Seminar, EuroHPC National Competence Centre Seminar Series, The Cyprus Institute.Talk
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"Deep learning in neutrino experiments" ( ZURICH, SWITZERLAND) Colloquium, Institute for Particle Physics and Astrophysics Colloquium, ETH Zurich.Archive
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"Machine learning in neutrino experiments" ( SHEFFIELD, UNITED KINGDOM) Seminar, Department of Particle Physics and Particle Astrophysics, University of Sheffield.Archive
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"Machine learning in neutrino experiments" ( STONY BROOK, UNITED STATES) Seminar, Department of Physics and Astronomy, Stony Brook University.Archive
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"Machine learning for neutrino identification" ( MEXICO CITY, MEXICO) Plenary conference talk, Symposium on Artificial Intelligence for Science, Industry and Society, UNAM.Slides
Public outreach talk at T3chFest (in Spanish)
Events organised
Highlighted awards and grants
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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".Details
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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".Details
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2025–26NERSC 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".Details
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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".Details
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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.Results
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Enrique Fuentes Quintana Award Funcas: national award for the best doctoral thesis in Engineering, Mathematics, Physics and Architecture.Details
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SCIE–Fundación BBVA Young Computer Science Research Award Awarded for international research experience, industry collaborations, and contributions to deep learning.Details
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Margarita Salas Research Award — Basic Sciences Madrid City Council: accésit for one of the best doctoral theses in Basic Sciences.Details
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UC3M Outstanding Doctoral Thesis Award Doctoral Programme in Computer Science and Technology, 2020–2021 cohort.Details
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UC3M Social Council Excellence Award — Alumni Recognising excellent professional development within three to five years of graduation.Details
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2016–17Spanish 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
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T3chFest Programming Contest First place in the individual algorithmic-programming contest, using Python; UC3M, Madrid.Results
Media & features
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ETH Zurich Physics Pretraining makes AI better at interpreting neutrino interactions
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ETH Zurich Partnerships A sharper eye for PET scanners
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ETH Zurich Physics Neutrinos caught on camera
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XLSemanal Saúl Alonso Monsalve, ingeniero informático: «Que existan estrellas, planetas... es uno de los grandes misterios de la ciencia»
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Cadena SER “Las condiciones en investigación en España no son las ideales”
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EL PAÍS Research about the universe leads to new cancer detection tools
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DUNE Faces of DUNE: Saúl Alonso-Monsalve
Contact
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Email
salonso "at" ethz.ch
saul.alonso.monsalve "at" cern.ch -
Office
HPK F 30, Hönggerberg campus
Otto-Stern-Weg 5, 8093 Zürich, Switzerland - Profiles