Improving the Performance of Volunteer Computing with Data Volunteers: A Case Study with the ATLAS@home Project. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón 001 (ICA3PP, 2016)

Analyzing the performance of volunteer computing for data intensive applications. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón Mateos (HPCS, 2016)

Fog computing through public-resource computing and storage. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón 001 (FMEC, 2017)

A new volunteer computing model for data-intensive applications. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón 001 (Concurr. Comput. Pract. Exp., 2017)

ComBos: A complete simulator of Volunteer Computing and Desktop Grids. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón 001 (Simul. Model. Pract. Theory, 2017)

Image-based model parameter optimisation using Model-Assisted Generative Adversarial Networks. - Saúl Alonso-Monsalve; Leigh H. Whitehead (CoRR, 2018)

A heterogeneous mobile cloud computing model for hybrid clouds. - Saul Alonso Monsalve; Félix García Carballeira; Alejandro Calderón 001 (Future Gener. Comput. Syst., 2018)

Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators. - Saúl Alonso-Monsalve; Andrés L. Suárez-Cetrulo; Alejandro Cervantes; David Quintana (Expert Syst. Appl., 2020)

WepSIM: An Online Interactive Educational Simulator Integrating Microdesign, Microprogramming, and Assembly Language Programming. - Félix García Carballeira; Alejandro Calderón Mateos; Saúl Alonso-Monsalve; Javier Prieto Cepeda (IEEE Trans. Learn. Technol., 2020)

Image-Based Model Parameter Optimization Using Model-Assisted Generative Adversarial Networks. - Saúl Alonso-Monsalve; Leigh H. Whitehead (IEEE Trans. Neural Networks Learn. Syst., 2020)

Analyzing the distributed training of deep-learning models via data locality. - Saúl Alonso-Monsalve; Alejandro Calderón 001; Félix García Carballeira; José Rivadeneira (PDP, 2021)

Artificial intelligence for improved fitting of trajectories of elementary particles in inhomogeneous dense materials immersed in a magnetic field. - Saúl Alonso-Monsalve; Davide Sgalaberna; Xingyu Zhao; Clark McGrew; André Rubbia (CoRR, 2022)

Automated Segmentation of Computed Tomography Images with Submanifold Sparse Convolutional Networks. - Saúl Alonso-Monsalve; Leigh H. Whitehead; Adam Aurisano; Lorena Escudero Sanchez (CoRR, 2022)

Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of neutrino interactions. - Saúl Alonso-Monsalve; Davide Sgalaberna; Xingyu Zhao; Adrien Molines; Clark McGrew; André Rubbia (CoRR, 2023)

AI-based particle track identification in scintillating fibres read out with imaging sensors. - Noemi Bührer; Saúl Alonso-Monsalve; Matthew Franks; Till Dieminger; Davide Sgalaberna (CoRR, 2024)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)