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WU Vienna University of Economics and Business

General Description

The WU Vienna University of Economics and Business (German: Wirtschaftsuniversität Wien, WU) is a public research university in Vienna, Austria, and is the largest university focusing on business, management, and economics in Europe. It has been ranked as one of the best business schools in Europe and received Triple accreditation (AACSB, EQUIS and AMBA). Vienna University of Economics and Business ranked 36th among more than 13,000 universities worldwide offering degrees in Business & Management in the 2022 QS World University Rankings by subject. WU has more than 20,000 students and over 400 researchers and lecturers, among those about 90 full professors. Research: The huge number of scientific staff create excellent research in many areas. 

Training: Besides the classical university lectures, the WU Executive Academy provides business-related education also in the form of Professional MBA and Executive MBA programs. Industry cooperation: WU is one of the main academic business contacts for all industry sectors within Austria and selected neighbour countries.


Priv.-Doz. Ing. Dr. Ronald Hochreiter (30%) is Docent at the Research Institute for Computational Methods and Co-program director of the Professional MBA program Digital Transformation and Data Science at WU Executive Academy. He has published 65 publications with almost 1000 citations. Role: Supervisory Board member, supervision of ESR 6, WP 2 Lead.

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Univ. Prof. Dr. Kurt Hornik (20%) is Professor of Statistics, Dean of the Department of Finance, Accounting and Statistics and Program Director of the MSc program Quantitative Finance. He has published more than 400 papers and received more than 35000 citations. Role: Supervision of ESR 5. 


Univ. Prof. Dr. Bettina Grün (10%) is Associate Professor of Statistics. She has published more than 150 papers and received more than 8000 citations. Role: Co-supervision of ESRs 5 and 6.

How we contribute to the MSCA:

WP 2 Lead. Contribute theoretical and applied expertise in building supervised and unsupervised ML systems, AI and financial technology, applied mathematical programming.

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