Pedro Casas-Hernandez

I am a researcher and expert in applied Artificial Intelligence, leading work at the intersection of AI/ML and real-world data analysis. My research focuses on two main domains: AI for Networking (AI4NETS) and AI for Industrial Applications (AI4Industry). In the AI4NETS space, I design and evaluate AI/ML models for network monitoring, anomaly detection, abuse and phishing detection, and QoE modeling – often leveraging graph neural networks and time-series foundation models. In the AI4Industry domain, I work on the conception and deployment of data-driven, AI-powered solutions tailored to industrial use-cases, aiming at cost reduction, operational efficiency, carbon footprint reduction, and enhanced productivity. Across both areas, my work emphasizes the development of robust, explainable, and scalable AI systems that address concrete challenges in complex environments.

I joined the AIT Austrian Institute of Technology Vienna in 2016, where I currently hold a Senior Scientist position in Data Science and Artificial Intelligence, at the Center for Digital Safety and Security. Between 2011 and 2015 I was Senior Researcher with the Telecommunications Research Center Vienna (FTW), working in Network Measurement and Analysis. Between 2003 and 2012 I held Research and Teaching Assistant positions at the Universidad de la República (UdelaR) in Montevideo, Uruguay, working in the core of the ARTES research group – Telecommunications Department, Electrical Engineering Institute.

I received an Electrical Engineering degree from the Engineering Faculty (FING) of UdelaR in 2005, working in the field of modeling and automatic assessment of Quality of Experience in multimedia networks. In 2010 I received a Ph.D. degree in Computer Science from Télécom Bretagne (ex. ENST Bretagne) in France, working in network anomaly detection and traffic analysis; in 2013 I received a Ph.D. in Electrical Engineering from Universidad de la República (UdelaR) in Uruguay. After my French Ph.D., I joined the French LAAS-CNRS research lab in Toulouse as a Postdoctoral Research Fellow, where I worked in machine learning techniques for network traffic monitoring and cybersecurity.

During the past 14 years I have been working as project manager, technical work leader and researcher in 32 different national and international projects, including both research and commercial projects. Besides industry-funded projects, I am currently acting as project coordinator and PI of the EU ERANET GRAPHS4SEC project, and coordinator and PI of the Austrian FFG AI4SimProd project.

I have published more than 230 peer-reviewed research papers in Network Measurement and Analysis topics at major international conferences, journals, and workshops (ACM PER, IEEE Network, IEEE TNSM, Computer Networks, ACM Multimedia, IEEE NETSOFT, IEEE CloudNET, IEEE CNSM, CoNEXT, SIGCOMM, INFOCOM, IFIP Networking, IFIP Performance, ITC, TMA), I have received 18 awards including best paper, best demo, best student work and best workshop awards (IEEE, IFIP, ACM, SIGCOMM SRC, ITC, EuroNGI European Network of Excellence), I have supervised four successfully concluded PhD students, three ongoing and 20 master students, interns and postdocs, and I have participated as teaching assistant and principal lecturer in different undergraduate, graduate, and postgraduate courses. I am also general chair of different conferences and workshops in network measurement and analysis, including machine learning-based networking workshops.

My main research interests include artificial intelligence, machine-learning, and data mining based approaches for Networking, AI-driven Industrial Analytics, Internet network measurements, network security and anomaly detection, as well as QoE modeling, assessment and monitoring.