Gabriele Scaffidi Militone

Argomento di ricerca

Cloud continuum machine learning

Tutori

• Daniele Apiletti
• Giovanni Malnati

Presentazione della ricerca

Poster

Corso di laurea magistrale

• Web Applications II. A.A. 2025/26, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Cloud Programming and Operations. A.A. 2025/26, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Web Applications II. A.A. 2024/25, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Mobile application development. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Web Applications II. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso

• MINDS - Machine Intelligence and Data Science Group (DAUIN)

• Rege Cambrin, Daniele; Scaffidi Militone, Gabriele; Colomba, Luca; Malnati, Giovanni; ... (2025)
  Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment. In: CV2: Computer Vision for Videogames Workshop at ECCV2024, Milan (ITA), September 29–October 4, 2024, pp. 374-389. ISSN 0302-9743. ISBN: 978-3-031-92386-9
  Contributo in Atti di Convegno (Proceeding)
• Scaffidi Militone, Gabriele; Apiletti, Daniele; Malnati, Giovanni (2024)
  Hermes, a low-latency transactional storage for binary data streams from remote devices. In: DATA & KNOWLEDGE ENGINEERING, vol. 153. ISSN 0169-023X
  Contributo su Rivista
• Militone, Gabriele Scaffidi; Apiletti, Daniele; Malnati, Giovanni (2023)
  Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models. In: 2023 IEEE International Conference on Big Data (BigData), Sorrento (IT), 15/12/2023 - 18/12/2023, pp. 3149-3153. ISBN: 979-8-3503-2445-7
  Contributo in Atti di Convegno (Proceeding)