New research platform "Data Science @ Uni Wien"
Starting in 2018, the new research platform "Data Science @ Uni Wien" under the supervision of Prof. Torsten Möller will be established for three years. The main focus of this platform is to bring together researchers from different areas of expertise to work on and solve various challenges that this new research field holds.
To this end, participants will primarily be driven by application problems whose solution requires novel methodological developments. The main research challenges that need to be tackled by this research platform can be summarized as
- application challenges,
- methodological challenges, and
- translational challenges.
The research platform specifically focuses on problems arising in
- Digital Humanities
- Financial Economics
- Industry 4.0
- Medical Sciences
While these areas are broad, they have things in common as they are data-driven and use similar methods from computer science, mathematics, and statistics.
Scientific research goals
Scientific research goals regarding the Methodological challenges focus in:
- Clustering Analysis
- Deep Neural Networks bei Compression
- High-dimensional Data Analysis
- Operations Research
Scientific research goals regarding the Translational challenges focus in:
- Communication of uncertainties
- Trust in a model
- Understanding trade-offs
- Understanding sensitivity
A further objective is to develop a training concept that will equip students with the appropriate methodological expertise in various application settings.
Find additional information at » univie.ac.at/research-platforms
Torsten Möller; Computer Science
João Alves; Earth Sciences, Geography and Astronomy
Tara Andrews ; Historical and Cultural Studies
Immanuel Bomze; Business, Economics and Statistics
Radu Ioan Bot ; Mathematics
Karl Dörner; Business, Economics and Statistics
Philipp Grohs; Mathematics
Nikolaus Hautsch; Business, Economics and Statistics
Hannes Leeb; Business, Economics and Statistics
Claudia Plant; Computer Science
Stefanie Rinderle-Ma ; Computer Science
Wolfgang Schmale ; Historical and Cultural Studies