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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 

  1. application challenges, 
  2. methodological challenges, and 
  3. translational challenges. 

The research platform specifically focuses on problems arising in 

  • Astronomy
  • 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
  • Optimization
  • Operations Research


Scientific research goals regarding the Translational challenges focus in:

  • Communication of uncertainties
  • Trust in a model
  • Understanding trade-offs
  • Understanding sensitivity
  • Comprehensibility

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

Participating scientists

Principal Investigator:

Torsten Möller; Computer Science

 

Participating Researchers:

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

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