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
Consulting Services
News
Team IDP
Publikationen
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Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,
2020.
In:
Proceedings of the Annual Conference of the PHM Society 2020.
12th Annual Conference of the PHM Society, virtual, 9-13 November 2020.
PHM Society.
Available from: https://doi.org/10.36001/phmconf.2020.v12i1.1205
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Meierhofer, Jürg; Homberger, Pascal,
2020.
Digitale Service Innovation in Wertschöpfungsnetzwerken : Anwendung im Getränkemarkt.
ServiceToday.
34(4), pp. 78-79.
Available from: https://doi.org/10.21256/zhaw-20827
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Herzog, Lisa; Murina, Elvis; Dürr, Oliver; Wegener, Susanne; Sick, Beate,
2020.
Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical Image Analysis.
65(101790).
Available from: https://doi.org/10.1016/j.media.2020.101790
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Müller, Marianne; Haenni Hoti, Andrea,
2020.
Item analysis of the KIDSCREEN-10 using Rasch modelling.
Health and Quality of Life Outcomes.
18(1), pp. 342-384.
Available from: https://doi.org/10.1186/s12955-020-01596-6
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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