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uva.nl
Dr M. Worring (1965) has been appointed professor of Data Science for Business Analytics at the University of Amsterdam's (UvA) Faculty of Economics and Business.
Prof Marcel Worring, professor Data Science for Business Analytics
Photo: Dirk Gillissen

Marcel Worring's research focuses on access to large-scale multimedia data sources. His approach centres on linking automatic data analyses with visualisations that provide insight into the data. In his work at the Faculty of Economics and Business, Worring will be exploring new methods for interpreting, modelling and strengthening business processes such as marketing and customer profiling using both unstructured data (images, text, social media) and structured data (business information, economic factors, demographic figures). The key question to be addressed is how computers can be made to automatically learn from this mass of information sources – with their differing qualities and characteristics – and how experts can shape that learning process with the aid of visualisations. In addition to his research activities, Worring will be teaching in the new Big Data Analytics track of the Master's in Econometrics.  

Prof. Marc Salomon, dean of the UvA's Amsterdam Business School, is pleased with Worring's appointment. 'The appointment of a computer scientist of Worring's high calibre at our business school will help to join the methods and technology side with the application side. That connection will be fundamental in expanding our scientific expertise in the field of Big Data.'

Worring has worked at the UvA since 1993. In 2003 he was appointed associate professor at the Informatics Institute, a position which he will now combine with his new appointment at the Faculty of Economics and Business. Worring is also associate director of Amsterdam Data Science, in which the UvA has partnered with the Amsterdam University of Applied Sciences (AUAS/HvA), the National Research Institute for Mathematics and Computer Science (CWI) and VU University Amsterdam to pursue interdisciplinary ICT research in data science.