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
-
Sariyar, Murat; Templ, Matthias,
2017.
Schulung zur Anonymisierung von personenbezogenen Datenbeständen.
In:
Schulung.
-
Meindl, Bernhard; Kowarik, Alexander; Templ, Matthias,
2017.
sdcApp : a shiny new GUI for sdcMicro[paper].
In:
NTTS New Techniques and Technologies for Statistics, Brussels, Belgium, 13-17 March 2017.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
pp. 1-4.
Available from: https://doi.org/10.21256/zhaw-4236
-
Meierhofer, Jürg,
2017.
Service value creation using data science[paper].
In:
Gumesson, Evert; Mele, Cristina; Polese, Francesco, eds.,
Service Logic, Network and Systems Theory and Service Science: Integrating three Perspectives for a New Service Agenda.
The 5th Naples Forum on Service, Sorrento, Naples, 6-9 June 2017.
Tricase:
Youcanprint Self-Publishing.
Available from: http://www.naplesforumonservice.it/uploads//files/Meierhofer.pdf
-
Templ, Matthias; Meindl, Bernhard; Kowarik, Alexander; Dupriez, Olivier,
2017.
Simulation of synthetic complex data: The R package simPop.
Journal of Statistical Software.
79(10), pp. 1-38.
Available from: https://doi.org/10.18637/jss.v079.i10
-
Kreutzmann, Ann-Kristin; Pannier, Sören; Rojas-Perilla, Natalia; Schmid, Timo; Templ, Matthias; Tzavidis, Nikos,
2017.
Small area estimation in R with application to Mexican income data[paper].
In:
NTTS New Techniques and Technologies for Statistics, Brussels, Belgium, 13-17 March 2017.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
pp. 1-5.
Available from: https://doi.org/10.21256/zhaw-4235