Pere Barlet-Ros

Pere Barlet-Ros is a Full Professor in the Department of Computer Architecture at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB) and the Barcelona Neural Networking Center (BNN-UPC). He leads research in AI-driven network technologies and is a key member of the UPC CBA and IDEAI-UPC research groups.

• Ph.D. in Computer Science, UPC (2008)
• M.Sc. in Computer Science, UPC (2003)

His research focuses on applying artificial intelligence, particularly graph neural networks, to solve critical challenges in network monitoring, traffic classification, congestion control, and cybersecurity. His work bridges theoretical innovation with practical deployment, as evidenced by integration into commercial tools like Auvik TrafficInsights and Talaia Polygraph. He explores digital twins for network optimization, privacy-preserving technologies, and next-generation web tracking detection.

The recent publications highlight a strong trend toward leveraging graph-based machine learning for network modeling, anomaly detection, and traffic compression. His work spans top-tier journals like IEEE/ACM Transactions on Networking and conferences such as IEEE EuroS&P and ACM SIGCOMM workshops, emphasizing robust, real-world AI/ML applications in networking.

• 2nd VALORTEC prize for best business plan (2014)
• Fiber Entrepreneurs award, best entrepreneur at FIB (2015)

Pere Barlet-Ros has served as Principal Investigator on seven competitive research projects and has advised at least 14 PhD students, including Paul Almasan, Miquel Ferriol, and Ismael Castell. His lab, BNN-UPC, fosters interdisciplinary collaboration in neural networking and AI for infrastructure. His entrepreneurial experience with Talaia Networks underscores a commitment to translating research into impactful technology.