Deep Learning at Scale. - Paolo Viviani 001; Maurizio Drocco; Daniele Baccega; Iacopo Colonnelli; Marco Aldinucci (PDP, 2019)

An Agent-Based Model to Support Infection Control Strategies at School. - Daniele Baccega; Simone Pernice; Pietro Terna; Paolo Castagno; Giovenale Moirano; Lorenzo Richiardi; Matteo Sereno; Sergio Rabellino; Milena Maria Maule; Marco Beccuti (J. Artif. Soc. Soc. Simul., 2022)

Living Along COVID-19: Assessing Contention Policies Through Agent-Based Models. - Daniele Baccega; Simone Pernice; Paolo Castagno; Matteo Sereno; Marco Beccuti (CIBB, 2023)

PHeP: TrustAlert Open-Source Platform for Enhancing Predictive Healthcare with Deep Learning. - Sandro Gepiro Contaldo; Emanuele Pietropaolo; Lorenzo Bosio; Simone Pernice; Irene Terrone; Daniele Baccega; Yuting Wang; Rahul Kumar Sahoo; Giuseppe Rizzo 002; Alessia Visconti; Paola Berchialla; Marco Beccuti (CIBB, 2024)

Epidemic Modelling Frameworks for Studying Infectious Disease Dynamics. - Daniele Baccega; Marco Beccuti; Simone Pernice; Irene Terrone (ICHI, 2025)

Exploiting GPU computing for effective Agent-Based simulation: initial experiments. - Marzio Pennisi; Giuliana Franceschinis; Daniele Baccega; Simone Pernice; Irene Terrone (PDP, 2025)

Social Compliance With NPIs, Mobility Patterns, and Reproduction Number: Lessons From COVID-19 in Europe. - Daniele Baccega; José Aguilar 001; Carlos Baquero; Antonio Fernández Anta; Juan Marcos Ramirez (IEEE Access, 2025)