Dr. Saúl Alonso-Monsalve

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 System Design, and Distributed Systems.

Experience

• Senior software engineer and researcher
  ETH Zürich, Zurich, Switzerland (Feb 2021 — present)

• Doctoral student
  CERN, Geneva, Switzerland (Feb 2018 — Jan 2021)

• Visiting student
  University of Cambridge, Cambridge, United Kingdom (Mar 2019 — Apr 2019)

• CERN openlab summer student
  CERN, Geneva, Switzerland (Jul 2017 — Sep 2017)

• Research and teaching assistant
  Universidad Carlos III de Madrid, Madrid, Spain (Jul 2015 — Jan 2018)

Selected publications

• "Contrastive learning for robust representations of neutrino data", Alex Wilkinson, Radi Radev, Saúl Alonso-Monsalve, Physical Review D, 2025.
  [Link]
• "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.
  [Link]
• "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.
  [Link]
• "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.
  [Link]
• "Automated Segmentation of Computed Tomography Images with Submanifold Sparse Convolutional Networks", Saúl Alonso-Monsalve, Leigh H. Whitehead, Adam Aurisano, Lorena Escudero Sanchez, arXiv pre-print, 2022.
  [Link]
• "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.
  [Link]
• "Neutrino interaction classification with a convolutional neural network in the DUNE far detector", B. Abi et al. (DUNE Collaboration), Physical Review D, 2020.
  [Link]
• "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.
  [Link]
• "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.
  [Link]

For a comprehensive list of publications, please refer to my profiles on:

Google Scholar ResearchGate ORCID Inspire HEP

Invited talks

• "Pushing the boundaries of neutrino physics with deep learning" (CALIFORNIA, USA) Seminar, SLAC National Accelerator Laboratory, Stanford University, May 8, 2025.
  [Link]
• "Machine learning methods for event reconstruction in accelerator neutrino experiments" (VENDÉE, FRANCE) Conference talk, 5th World Summit on Exploring the Dark Side of the Universe (EDSU2024), Île de Noirmoutier, Jun 2-7, 2024.
  [Link]
• "Artificial intelligence and machine learning in neutrino physics" (NAPLES, ITALY) Conference talk, 22nd International Workshop on Next Generation Nucleon Decay and Neutrino Detectors (NNN23), Procida, Oct 11-13, 2023.
  [Link]
• "Computer vision introduction" (CALIFORNIA, USA) Lecture, SLAC Summer Institute, SLAC National Accelerator Laboratory, Stanford University, Aug 7-18, 2023.
  [Link]
• "Machine learning for neutrino experiments" (TOKYO, JAPAN) Seminar, Kavli Institute for the Physics and Mathematics of the Universe (IPMU), University of Tokyo, Jul 6, 2023.
  [Link]
• "Machine learning and high-performance computing for neutrino oscillations" (NICOSIA, CYPRUS) Seminar, EuroHPC National Competence Centre, The Cyprus Institute, Oct 18, 2022.
  [Link]
• "Deep learning in neutrino experiments" (ZURICH, SWITZERLAND) Colloquium, Institute for Particle Physics and Astrophysics, ETH Zurich, Nov 3, 2020.
  [Link]
• "Machine learning in neutrino experiments" (SHEFFIELD, ENGLAND) Seminar, Department of Particle Physics and Particle Astrophysics, University of Sheffield, Nov 18, 2019.
  [Link]
• "Machine learning in neutrino experiments" (NEW YORK, USA) Seminar, Department of Physics and Astronomy, Stony Brook University, Oct 28, 2019.
  [Link]
• "Machine learning for neutrino identification" (MEXICO CITY, MEXICO) Plenary conference talk, Symposium on Artificial Intelligence for Science, Industry and Society, UNAM, Oct. 21-25, 2019.
  [Link]


Public outreach talk at T3chFest (in Spanish):

Events organised

Neutrino Physics and Machine Learning (NPML 2024)
International Workshop, 79 participants, Jun. 25-28, 2024.
[Link]

IPA workshop on Machine Learning for particle physics and astrophysics (IPA-ML)
Internal Workshop, 105 participants, Mar. 20-22, 2023.
[Link]

Highlighted awards and grants

AI for Science (AI4Sci@NERSC) grant (Principal investigator)
NERSC (Lawrence Berkeley National Laboratory, CA, USA): 5,000 GPU compute-node hours for the project "Deep Learning for Neutrino Event Reconstruction", 2025.
[Link]

Enrique Fuentes Quintana award
Funcas Organization, for the best Spanish doctoral thesis within the fields of Engineering, Mathematics, Physics and Architecture, Dec 2022.
[Link]

Spanish Computer Science Society (SCIE) award
BBVA Foundation, for young computer science researchers, for the distinguishing, innovative, and relevant doctoral work, Nov 2022.
[Link]

Margarita Salas award
Madrid City Council, accessit for one of the best doctoral theses in the field of basic sciences, Nov 2022.
[Link]

Outstanding thesis award
Universidad Carlos III de Madrid: for the unique merits and values of the doctoral thesis, 2021.
[Link]

Excellence award
Social Council, Universidad Carlos III de Madrid, Former students (Alumni): for the excellent professional development carried out between 3 and 5 years after graduation, 2021.
[Link]

Hackathon winner
CERN Webfest, 2^nd prize, App: "Guess what particle", Jul 2018.
[Link]

National parallel programming contest winner
Sociedad Arquitectura y Tecnología de Computadores, Jornadas Sarteco (programming tasks using OpenMP, MPI, and CUDA), 2^st prize (Málaga 2017), 3^st prize (Salamanca 2016).
[Link]

Programming contest winner
T3chFest UC3M, 1^st prize (algorithmics using Python), Madrid, Feb 2016.
[Link]

Contact

Email: salonso "at" ethz.ch / saul.alonso.monsalve "at" cern.ch

Office: HPK F 30 (Hönggerberg campus), Otto-Stern-Weg 5, 8093 Zürich, Switzerland.

LinkedIn: GitHub:

Press: EL PAÍS [English] [Spanish] Cadena SER [Spanish] XLSemanal [Spanish]