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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Cieliebak, Mark; Drewek, Anna; Jakob Grob, Karin; Kruse, Otto; Mlynchyk, Katsiaryna; Rapp, Christian; Waller, Gregor,
2023.
Winterthur:
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-2491
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Steiner, Albert; Weingart, Joel Niklas; Huber, Marius; Scherrer, Maike,
2023.
The effect of coopetition on driving distance in logistics in urban areas[poster].
In:
5th VREF Conference on Urban Freight, Gotenburg, Sweden, 18-20 October 2023.
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Wulf, Jochen; Meierhofer, Jürg,
2023.
Large Language Models in Industrieunternehmen.
Technische Rundschau.
23(9), pp. 48-50.
Available from: https://doi.org/10.21256/zhaw-28949
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Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach,
2023.
Fully unsupervised fault detection in solar power plants using physics-informed deep learning[paper].
In:
Brito, Mário P.; Aven, Terje; Baraldi, Piero; Čepin, Marko; Zio, Enrico, eds.,
Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023).
33rd European Safety and Reliability Conference (ESREL), Southampton, United Kingdom, 3-7 September 2023.
Singapore:
Research Publishing.
pp. 1737-1745.
Available from: https://doi.org/10.3850/978-981-18-8071-1_P652-cd
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2023.
Assessing keyness using permutation tests.
arXiv.
Available from: https://doi.org/10.48550/arXiv.2308.13383