Cristian Bosch

About

Cristian is a senior research data scientist in CeADAR, Ireland’s national centre for Applied AI. He joined CeADAR as a Marie Curie COFUND fellow in 2017, with a project studying data-driven predictive maintenance in wind turbines. His has gained strong expertise on Time Series analysis, deep learning techniques, computer vision and Natural Language Processing.
His educational background is as a physicist, as he studied Degree in Physics, a Masters degree in Nanotechnology and a PhD in Theoretical Physics in the University of Valencia (Spain). During that time, his research left contributions in the fields of Quantum Computation realisation and Beyond
Standard Model Physics. Cristian's research path began as an undergraduate with three introductory grants given by the Spanish Research Council (CSIC) and the Spanish Ministry of Education, followed by the CERN Summer Student fellowship (2010) and the PhD fellowship from the Spanish Ministry of Education. He has conducted research at CERN (Switzerland) and Fermilab (US) and published in major particle physics journals and has participated in national and international conferences.

Employment

• CeADAR - University College Dublin Senior Research Data Scientist
  2022 - Present
• CeADAR - University College Dublin Data Scientist II
  2021 - 2022
• CeADAR - University College Dublin Marie Sklodowska-Curie COFUND Research Fellow
  2018 - 2021
• Universitat de València Research and teaching staff
  2012 - 2015

Education

• Universidad de Valencia PhD in Theoretical Physics
  2012 - 2017
• Universidad de Valencia Master degree in Molecular Nanoscience and Nanotechnology
  2010 - 2012
• Universidad de Valencia Five-year degree in Physics
  2005 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• Biomarker-targeted functionalized magnetic nanoparticles: synthesis and aptamer conjugation optimization toward Alzheimer's disease biosensing
  Nanoscale Advances 2026 DOI: 10.1039/D6NA00021E
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• Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning
  Proceedings of the 3rd International Workshop on AI for Quantum and Quantum for AI (AIQxQIA 2025) co-located with the 28th European Conference on Artificial Intelligence (ECAI 2025), Bologna, Italy, O… 2025
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• Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts
  CoRR 2025 DOI: 10.48550/ARXIV.2511.11743
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• xSTAE: Explaining Classifier Decisions through EEG Signal Style Transfer Autoencoding
  Proceedings of the Second Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2025) co-located with 28th European Conference on Artificial Intelligence (ECAI 2025), Bologna, … 2025
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• $$ Xpression $$: A Unifying Metric to Optimize Compression and Explainability Robustness of AI Models
  2024 DOI: 10.1007/978-3-031-63787-2_19
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• Perspective Chapter: Computation of Wind Turbine Power Generation, Anomaly Detection and Predictive Maintenance
  Computational Semantics 2023 DOI: 10.5772/intechopen.109698
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• Machine Learning for Wind Turbine Fault Prediction through Combination of Same Type Turbine Datasets
  Materials Research Proceedings 2022
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• Composite states of two right-handed neutrinos
  Phys. Rev. D 2016 DOI: 10.1103/PhysRevD.94.116019
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• Discarding a 125 GeV heavy Higgs in an {MSSM} model with explicit CP-violation
  Nuclear and Particle Physics Proceedings 2016 DOI: http://dx.doi.org/10.1016/j.nuclphysbps.2015.09.090
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• Flavor-changing Higgs boson decays into bottom and strange quarks in supersymmetric models
  Phys. Rev. D 2015 DOI: 10.1103/PhysRevD.92.095017
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