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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2018.
Industrie 4.0 : Perspektiven durch neue Service-Modelle.
Topsoft-Magazin.
18(1), pp. 18-19.
Available from: https://issuu.com/topsoft/docs/tsm18-1
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Kavassalis, Petros; Stieber, Harald; Breymann, Wolfgang; Saxton, Keith; Gross, Francis Joseph,
2018.
An innovative RegTech approach to financial risk monitoring and supervisory reporting.
Journal of Risk Finance.
19(1), pp. 39-55.
Available from: https://doi.org/10.1108/JRF-07-2017-0111
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Filzmoser, Peter; Hron, Karel; Templ, Matthias,
2018.
Applied compositional data analysis : with worked examples in R.
1. Auflage.
Cham:
Springer.
Springer Series in Statistics (SSS).
ISBN 978-3-319-96420-1.
Available from: https://doi.org/10.1007/978-3-319-96422-5
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2018.
Ausbildung zur Führungskraft in der Instandhaltung an der Hochschule.
fmpro service.
2018(3), pp. 14-16.
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Chen, Yann Qi; Fink, Olga; Sansavini, Giovanni,
2018.
IEEE Transactions on Industrial Electronics.
65(1), pp. 561-569.
Available from: https://doi.org/10.1109/TIE.2017.2721922