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
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
-
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.
-
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
-
2020.
Die Konvergenz von Digitalisierung und Servitisierung in der Industrie 4.0.
Aktuelle Technik.
2020(8), pp. 32.
Available from: https://doi.org/10.21256/zhaw-20432
-
Sauermann, Stefan; Kanjala, Chifundo; Templ, Matthias; Austin, Claire C.,
2020.
Preservation of individuals’ privacy in shared COVID-19 related data.
SSRN.
Available from: https://doi.org/10.2139/ssrn.3648430
-
Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Manninen, Jaakko; Goren Huber, Lilach,
2020.
Early fault detection based on wind turbine SCADA data using convolutional neural networks[paper].
In:
PHME 2020 : Proceedings of the 5th European Conference of the PHM Society.
5th European Conference of the Prognostics and Health Management Society, Virtual Conference, 27-31 July 2020.
PHM Society.
Available from: https://doi.org/10.36001/phme.2020.v5i1.1217