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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2020.
Algorithmic Fairness : Algorithmen und soziale Gerechtigkeit.
Inside IT.
Available from: https://www.inside-it.ch/post/dsi-insights-algorithmic-fairness-algorithmen-und-soziale-gerechtigkeit-20200110
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Loi, Michele; Heitz, Christoph; Christen, Markus,
2020.
A comparative assessment and synthesis of twenty ethics codes on AI and big data[paper].
In:
7th Swiss Conference on Data Science, Lucerne, Switzerland, 26 June 2020.
IEEE.
pp. 41-46.
Available from: https://doi.org/10.1109/SDS49233.2020.00015
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Templ, Matthias; Templ, Barbara,
2020.
Analysis of chemical compounds in beverages : guidance for establishing a compositional analysis.
Food Chemistry.
325(126755).
Available from: https://doi.org/10.1016/j.foodchem.2020.126755
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Templ, Matthias,
2020.
Anonymisierung von personenbezogenen Daten.
In:
Winterkongress der Digitalen Gesellschaft, Zürich, 22. Februar 2020.
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Christen, Markus; Heitz, Christoph; Kleiber, Tom; Loi, Michele,
2020.
Code of ethics for data-based value creation.
Thun:
Swiss Alliance for Data-Intensive Services.
ISBN 978-3-9522703-3-2.
Available from: https://doi.org/10.21256/zhaw-24226