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 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
Team IDP
Publikationen
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Schmid, Daniel; Herrmann, Thomas,
2024.
Human-zentrierte und resilienzfördernde Digitalisierung.
ZHAW Industrie 4.0.
Available from: https://blog.zhaw.ch/industrie4null/2024/04/09/human-zentrierte-und-resilienzfoerdernde-digitalisierung/
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Jaeggi, Jessica S.; Achermann, Basil; Lorenzetti, Silvio R.,
2024.
Journal of Functional Morphology and Kinesiology.
9(2), pp. 68.
Available from: https://doi.org/10.3390/jfmk9020068
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Halman, Nir; Sedding, Helmut A.,
2024.
A faster FPTAS for makespan minimization with time-dependent agreeable V-shaped processing times[paper].
In:
Proceedings of the 19th International Workshop on Project Management and Scheduling.
19th International Workshop on Project Management and Scheduling (PMS), Bern, Switzerland, 2-5 April 2024.
University of Bern.
Available from: https://doi.org/10.21256/zhaw-30440
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Oberhofer, Katja; Knopfli, Céline; Achermann, Basil; Lorenzetti, Silvio,
2024.
Sports.
12(4).
Available from: https://doi.org/10.3390/sports12040092
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Scantamburlo, Teresa; Baumann, Joachim; Heitz, Christoph,
2024.
On prediction-modelers and decision-makers : why fairness requires more than a fair prediction model.
AI & Society.
Available from: https://doi.org/10.1007/s00146-024-01886-3