Gyözö Gidofalvi is an Associate Professor at the Division of Geoinformatics at the Department for Urban Planning and Environment as well as Leader of the Efficient Transport Concepts research area and recently the Urban Good Distribution research program at the Integrated Transport Research Lab (ITRL https://www.itrl.kth.se/) at the Royal Institute of Technology (KTH) in Stockholm, Sweden. His main research interests include include big mobility data analytics and artificial intelligence for transport infrastructure and operations optimization, travel survey methods, travel behavior modeling, traffic management, spatio-temporal data mining and analysis, Location-Based Services (LBS), locations privacy, Intelligent Transportation Systems (ITS), and related GIS areas such as web and mobile GIS and spatial databases.
Previously, Gyözö has been a Postdoctoral Fellow at the Uppsala Database Laboratory (UDBL) at the Department of Information Technology, Uppsala University, where he was involved in the iStreams project, where his task was to develop methods and tools for analyzing and mining high-volume industrial data streams. During his industrial Ph.D. study at Geomatic a/s and Aalborg University, he has been focusing on developing Spatio-Temporal Data Mining Methods for Location-Based Services. During his M.Sc. study at the University of California, San Diego, he has been mainly focusing on financial text mining, but he also has had some experience in connectionist learning methods, genetic algorithms, statistical learning methods, and computer vision.