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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2016.
Instandhaltung im Zeitalter von Industrie 4.0.
fmpro service.
2016(1), pp. 4-6.
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Hu, Yang; Palmé, Thomas; Fink, Olga,
2016.
Maximal information-based nonparametric exploration for condition monitoring data[paper].
In:
PHME16 : Proceedings of the Third European Conference of the Prognostics and Health Management Society 2016.
3rd European Conference of the PHM Society (PHME16), Bilbao, Spain, 5-8 July 2016.
PHM Society.
pp. 419-425.
Available from: https://doi.org/10.21256/zhaw-2755
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2016.
In:
Joint Spring Conference 2016 of E-Finance Lab and IBM: "Identifiers and Identification Management in the Financial World and Beyond – Requests, Solutions, and Applications", Frankfurt, Germany, 16 February 2016.
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Hu, Yang; Fink, Olga; Palme, Thomas,
2016.
Online sequential extreme learning machines for fault detection[paper].
In:
2016 IEEE International Conference on Prognostics and Health Management (ICPHM).
IEEE International Conference on Prognostics and Health Management (ICPHM 2016), Ottawa, Canada, 20-22 June 2016.
IEEE.
Available from: https://doi.org/10.1109/ICPHM.2016.7542841
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Wildi, Marc; McElroy, Tucker,
2016.
Optimal real-time filters for linear prediction problems.
Journal of Time Series Econometrics.
8(2), pp. 155-192.
Available from: https://doi.org/10.1515/jtse-2014-0019