The SmartData@PoliTO center focuses on Big Data technologies, Data Science and Machine Learning approaches. We blend interdisciplinary people and competences from different domains to provide cross-domain solutions to the widest spectrum of knowledge discovery challenges, by leveraging advanced expertise in data science, from data management, to data modeling, analytics, and engineering. We are a well-recognized center where experts in methodologies and domain experts from various disciplines work in a single space, facing both theoretical problems and helping companies toward applications.
Presenter: Andrea SordelloThursday, June 19th, 2025, 5:00 PMLocation: Sala Grande Covivio, Corso Ferrucci 112 ABSTRACT Passive network measurement traditionally emphasizes inbound traffic for detecting threats and monitoring performance. Outbound traffic generated by internal hosts that fail to reach valid destinations or contains error messages remains largely unexplored. We investigate the potential of such traffic to […]
Presenter: Kai HuangThursday, June 5th, 2025, 5:00 PMLocation: Sala Grande Covivio, Corso Ferrucci 112 ABSTRACT The rapid evolution of cyber threats and the increasing sophistication of cyberattacks have made digital forensics a cornerstone of modern cybersecurity. In this context, Large Language Models (LLMs) present a compelling opportunity to augment cybersecurity forensics. To investigate the capabilities […]
On May 20th 2025 at 16:00, in Luigi Ciminiera meeting room, Politecnico di Torino, the SmartData@Polito Center will host the companies associated with the Digital Technologies Group of Unione Industriali Torino, a Group that includes about 170 companies, with over 12 thousand collaborators, that enable and support the digital transition of the economy: from TLC […]
Presenter: Pierrick LeroyThursday, May 8th, 2025, 5:00 PMLocation: Sala Grande Covivio, Corso Ferrucci 112 ABSTRACT Face Recognition (FR) tasks have significantly progressed with the advent of Deep Neural Networks, particularly through margin-based triplet losses that embed facial images into high-dimensional feature spaces. During training, these contrastive losses focus exclusively on identity information as labels. However, […]
