Floragasse 7 – 5th floor, 1040 Vienna
Subscribe to our Newsletter

Andreas Rauber

Andreas Rauber

is key researcher at SBA Research and Associate Professor at TU Wien.

Research Interests

Andreas’ research interests cover the broad scope of digital libraries and information spaces, including specifically text and music information retrieval and organization, information visualization, as well as data analysis, neural computation and digital preservation.


Andreas is Associate Professor at the Department of Information and Software Engineering (ifs) at TU Wien. He furthermore is president of AARIT, the Austrian Association for Research in IT and a Honorary Research Fellow in the Department of Humanities Advanced Technology and Information Institute (HATII), University of Glasgow. He received his master’s degree and PhD in Computer Science from TU Wien in 1997 and 2000, respectively. In 2001 he joined the National Research Council of Italy (CNR) in Pisa as an ERCIM Research Fellow, followed by an ERCIM Research position at the French National Institute for Research in Digital Science and Technology (INRIA), at Rocquencourt, France, in 2002. From 2004-2008 he was also head of the iSpaces research group at the eCommerce Competence Center (ec3).

In 1998 he received the ÖGAI Award of the Austrian Society for Artificial Intelligence (ÖGAI), and the Cor-Baayen Award of the European Research Consortium for Informatics and Mathematics (ERCIM) in 2002. He has published numerous papers in refereed journals and international conferences and served as PC member and reviewer for several major journals, conferences and workshops. He is a member of the Association for Computing Machinery (ACM), The Institute of Electrical and Electronics Engineers (IEEE), the Austrian Society for Artificial Intelligence (ÖGAI). He serves on the board of the IEEE Technical Committee on Digital Libraries (TCDL), and was a member of the DELOS Network of Excellence on Digital Libraries as well as the MUSCLE Network of Excellence on Multimedia Understanding through Semantics, Computation and Learning.