Invited Paper

MLNET: Machine Learning Models for Network Analytics
 Pedro Casas Pedro Casas is Scientist at the Austrian Institute of Technology (AIT) in Vienna, working in ICT Security and Information Management. He received an Electrical Engineering degree from Universidad de la República (UdelaR), Uruguay in 2005, and a Ph.D. degree in Computer Science from Institut Mines-Télécom, Télécom Bretagne, France in 2010. He held a Research and Teaching Assistant position at UdelaR between 2003 and 2012, and was at the research lab LAAS-CNRS in Toulouse as a Postdoctoral Research Fellow between 2010 and 2011. Between 2011 and 2015 he was Senior Researcher at the Telecommunications Research Center Vienna (FTW). His research areas span the monitoring and analysis of network traffic, machine learning and big data based approaches for Networking, network security and anomaly detection, as well as QoE modeling and assessment. Dr. Casas works as project manager, Ph.D. supervisor, technical work leader and researcher in multiple international research and industry-related projects, he has published more than 120 networking research papers in major international conferences and journals, has received eight best paper and best workshop awards, and is the general chair of different network measurement workshops and conferences, including TMA Conference 2018, and the ACM SIGCOMM Big-DAMA and Internet-QoE workshops' series.