Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems. - Oliver J. Fisher; Nicholas James Watson; Josep Escrig; Rob Witt; Laura Porcu; Darren Bacon; Martin Rigley; Rachel L. Gomes (Comput. Chem. Eng., 2020)

Intelligent Industrial Cleaning: A Multi-Sensor Approach Utilising Machine Learning-Based Regression. - Alessandro Simeone; Elliot Woolley; Josep Escrig; Nicholas James Watson (Sensors, 2020)

CARAMEL: results on a secure architecture for connected and autonomous vehicles detecting GPS spoofing attacks. - Christian Vitale; Nikos Piperigkos; Christos Laoudias; Georgios Ellinas; Jordi Casademont; Josep Escrig; Andreas Kloukiniotis; Aris S. Lalos; Konstantinos Moustakas; Rodrigo Diaz Rodriguez; Daniel Baños; Gemma Roqueta Crusats; et al. (EURASIP J. Wirel. Commun. Netw., 2021)

Analysis of Vehicular Scenarios and Mitigation of Cell Overload due to Traffic Congestions. - Martín Trullenque Ortiz; Oriol Sallent; Daniel Camps-Mur; Josep Escrig; Carlos Herranz (VTC Spring, 2022)

On Alleviating Cell Overload in Vehicular Scenarios. - Martín Trullenque Ortiz; Oriol Sallent; Daniel Camps-Mur; Josep Escrig; Carlos Herranz-Claveras; Jad Nasreddine; Jordi Pérez-Romero (VTC Fall, 2022)

A Real-World Dataset for Benchmarking False Alarm Rate in Keyword Spotting. - Sergi Sánchez Deutsch; Ivan Huerta Casado; Josep Escrig (CCIA, 2023)

Inter-Satellite Link Prediction with Supervised Learning Based on Kepler and SGP4 Orbits. - Estel Ferrer; Joan Adrià Ruiz-de-Azua; Josep Escrig (CCIA, 2023)

A Data-driven Approach for Risk Exposure Analysis in Enterprise Security. - Albert Calvo; Santiago Escuder; Josep Escrig; Marta Arias; Nil Ortiz; Jordi Guijarro (DSAA, 2023)

Achieving High-Fidelity Explanations for Risk Exposition Assessment in the Cybersecurity Domain. - Albert Calvo; Santiago Escuder; Josep Escrig; Xavier Marrugat-Plaza; Nil Ortiz; Jordi Guijarro (eCrime, 2023)

Inter-Satellite Link Prediction for Non-Terrestrial Networks Using Supervised Learning. - Estel Ferrer; Josep Escrig; Joan Adrià Ruiz-de-Azua (EuCNC/6G Summit, 2023)

Towards IoT Ambient Intelligence for Industry 4.0. - Marisa Catalan; Mohamad Hjeij; Aleix Boixader; Percy Bonett; Mario Montagud; Josep Escrig; Josep Brugués; Toni Adame; Carlos Labella; Iván Huerta; Miguel Urias (FiCloud, 2023)

On the Application of Q-learning for Mobility Load Balancing in Realistic Vehicular Scenarios. - Martín Trullenque Ortiz; Oriol Salient; Daniel Camps-Mur; Josep Escrig; Jad Nasreddine; Jordi Pérez-Romero (VTC2023-Spring, 2023)

Optimizing Energy Consumption of Kubernetes Clusters with Deep Reinforcement Learning. - Josep Escrig; Adriana Fernández-Fernández; Rizkallah Touma (CCIA, 2024)

Automatic Catalan Keyword Spotting Database Generator. - Alex Sánchez; Sergio Montoya; Josep Escrig; Iván Huerta (CCIA, 2024)

Inter-Satellite Link Prediction with Supervised Learning Based on Kepler and SGP4 Orbits. - Estel Ferrer; Joan Adrià Ruiz-de-Azua; Francesc Betorz; Josep Escrig (Int. J. Comput. Intell. Syst., 2024)

RBD24 : A labelled dataset with risk activities using log application data. - Albert Calvo; Santiago Escuder; Nil Ortiz; Josep Escrig; Maxime Compastié (Comput. Secur., 2025)