Institute of Data Analysis and Process Design (IDP)
We create value from data
We use advanced data-based methods to create innovative solutions for business and industry. We address real-life challenges with scientific methods and a strong commitment to practicability. We are the leading educator and partner of choice for applied data science and business engineering in Switzerland.
Research Groups

Advanced scientific tools for solutions in the financial industry

Health and Envrionmental Analytics
Health and Environmental Analytics
Analyzing data to derive interpretable results using statistical and machine learning techniques

Maintenance, Mobility, AI & Society
Leverage AI and advanced modeling for innovations in predictive maintenance, mobility solutions, and socially aligned systems

Generating insights, creating value and fostering innovation in business processes and services

Visual Intelligence and Applications
As visual data becomes one of the most abundant and complex sources of information, Visual Intelligence is a key pillar of modern data science — enabling new ways to analyze, model, and communicate through images, video, and immersive environments
For Students
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Team IDP
Publikationen
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Weber, Maurice; Renggli, Cedric; Grabner, Helmut; Zhang, Ce,
2020.
Observer dependent lossy image compression[paper].
In:
42nd German Conference on Pattern Recognition (DAGM-GCPR), virtual, 28 September - 1 October 2020.
Available from: https://doi.org/10.48550/arXiv.1910.03472
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2020.
Scheduling jobs with a V-shaped time-dependent processing time.
Journal of Scheduling.
23(6), pp. 751-768.
Available from: https://doi.org/10.1007/s10951-020-00665-4
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Meierhofer, Jürg; Dobler, Martin; Frick, Klaus; Schweiger, Lukas,
2020.
Smart service patterns for small manufacturing enterprises[paper].
In:
Bigdeli, Ali; Baines, Tim, eds.,
Proceedings of the Spring Servitization Conference : Advanced Services for Sustainability and Growth.
Spring Servitization Conference "Advanced Services for Sustainability and Growth", Online, 14-16 September 2020.
Birmingham:
Aston University.
pp. 88-95.
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West, Shaun; Meierhofer, Jürg; Stoll, Oliver; Schweiger, Lukas,
2020.
Value propositions enabled by digital twins in the context of servitization[paper].
In:
Bigdeli, Ali; Baines, Tim, eds.,
Proceedings of the Spring Servitization Conference : Advanced Services for Sustainability and Growth.
Spring Servitization Conference "Advanced Services for Sustainability and Growth", Online, 14-16 September 2020.
Birmingham:
Aston University.
pp. 152-160.
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Müller, Marianne,
2020.
Item fit statistics for Rasch analysis : can we trust them?.
Journal of Statistical Distributions and Applications.
7(5).
Available from: https://doi.org/10.1186/s40488-020-00108-7