Raubal Martin
Professor
Dept. of Civil, Environmental and Geomatic Engineering
ETH Zürich - Eidgenössische Technische Hochschule Zürich - Swiss Federal Institute of Technology in Zurich
Switzerland
Biography
Martin Raubal has been a Professor of Geoinformation Engineering in the Department of Civil, Environmental and Geomatic Engineering at the Institute of Cartography and Geoinformation since April 2011. He was born in Vienna, Austria, in 1968. Professor Raubal studied spatial information science and engineering at the University of Maine, Orono, ME, USA. He obtained a Master’s degree in 1997 before going on to study surveying engineering at the Vienna University of Technology in Austria, where he received an engineering diploma (M.S.) in 1998. He was awarded a PhD (Dr. techn.) from the same university in 2001. Later, he moved to the University of Münster, Germany, to obtain a professorship in geoinformatics in 2006. Prior to joining ETH Zurich, he was an Associate Professor and Vice-Chair at the Department of Geography at the University of California, Santa Barbara, USA.
Research Interest
Martin Raubal’s main research interest is geographic information science, specialising in mobile geographic information systems (GIS) and spatial information technologies. His research group studies how people use location-based, mobile spatial information in decision-making processes – such as in tourism or communication. The group focuses on GIS and location-based services (LBS), which include navigation devices, information and emergency services, or generally services that provide the user with information on the current location. Geoinformation and location-based data is pivotal in the mobile information society for the safety and wellbeing of its citizens. This goes for many areas, such as public transport, environmental protection, planning, disaster management, agriculture and forestry, information and communication technologies, and education. Against this backdrop, Martin Raubal’s group develops mobile eye-tracking cognitive techniques and methods suitable for the analysis, representation and modelling of the spatio-temporal behaviour of people.