Third Ceiden-UPM Workshop: “Machine Learning in Nuclear Science and Technology Applications”


14 May 2021, from 09:00 to 13:00h.

Review of the event (Spanish)


Introduction and Program

Tadahiro Kin (Kyushu University, Japan) – “ML in radiation metrology: Application of Gamma-ray spectrometry”

Berenguer Bríquez (Tecnatom) – “Machine Learning in Nuclear Science and Technology Applications”

Adrián Sánchez (CIEMAT) – “Deep Learning applied to Capture Cross Section Data Analysis”

Aris Villacorta (CIEMAT) – “Unsupervised Learning for nuclear fuel cycle applications

Emilio Mendoza (CIEMAT) – “Machine learning applied to modelling of nuclear deexcitation cascades”

Arnau Albà (Paul Scherrer Institut, Switzerland) – “Surrogate Models for Uncertainties on Decay Heat and Nuclide Inventory in Nuclear Depletion Calculations”

Ahmed Shama (Paul Scherrer Institut) – “Predicting the Bias in Calculations of Spent Nuclear Fuel Characteristics”

Joachim Hansson (Uppsala University, Sweden) – “Gaussian Processes and Levenberg-Marquardt”

Virginie Solans (Uppsala University, PSI) – “Optimization of spent fuel canister loading using a neural network and genetic algorithm”

INGENIA UPM – “Machine Learning techniques in V&V of Nuclear Data Bases”

INGENIA UPM – “Machine learning in Reactor-oriented applications”

Norberto Sebastián Schmidt (Bariloche Atomic Center, Argentina) – “Neutron and gamma beam simulation using OpenMC and Python’s libraries for Machine Learning”

Denise Neudecker (Los Alamos National Laboratory, USA) – “Using Machine Learning Algorithms for Large-scale Nuclear-data Validation”

Georg Schnabel (IAEA) – “Annonuncement of Technical Meeting AI4Atoms”

Summary record