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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2024.
Kann die KI bei der Fehlererkennung unter realen Bedingungen helfen?.
fmpro service.
(4), pp. 6-7.
Available from: https://doi.org/10.21256/zhaw-31758
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Weisskopf, Simon Alexander; Meierhofer, Jürg; Sordini, Furio Valerio,
2024.
Quantitative models for sustainable smart services in the building industry[paper].
In:
West, Shaun; Meierhofer, Jürg; Buecheler, Thierry, eds.,
Smart Services Summit : building resilience in a changing world.
Sixth Smart Services Summit, Zurich, Switzerland, 27 Oktober 2023.
Cham:
Springer.
pp. 29-41.
Available from: https://doi.org/10.1007/978-3-031-60313-6_3
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Drewek, Anna; Ordelt, Christian; Riahi, Nima; Sedding, Helmut,
2024.
100 Jahre Sollzeiten - Ein Konzept für die Zukunft?.
Logistics Innovation.
2024(1), pp. 10-13.
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Thouvenin, Florent; Volz, Stephanie; Weiner, Soraya; Heitz, Christoph,
2024.
Jusletter IT.
Available from: https://doi.org/10.38023/9642ed9a-5c05-4884-b5b9-ebc66f2f3324
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Wulf, Jochen; Meierhofer, Jürg,
2024.
Towards a taxonomy of Large Language Model based business model transformations[paper].
In:
West, Shaun; Meierhofer, Jürg; Buecheler, Thierry, eds.,
Smart Services Summit : Building Resilience in a Changing World.
Smart Services Summit, Zurich, Switzerland, 23 October 2023.
Cham:
Springer.
pp. 119-131.
SMSESU 2023. Progress in IS.
Available from: https://doi.org/10.1007/978-3-031-60313-6_9