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 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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2019.
Scheduling with asymmetric piecewise-linear time-dependent processing times[paper].
In:
Proceedings of the 14th Workshop on Models and Algorithms for Planning and Scheduling Problems, MAPSP 2019.
MAPSP 2019, Renesse, The Netherlands, 2-7 June 2019.
Maastricht University.
pp. 43-45.
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2019.
Service Transformation und Service Engineering (AP3).
In:
Thiel, Christian, ed.,
Nutzenbasierter Digitalisierungsnavigator : wie KMU ihre Digitalisierungsstrategie selbst entwickeln können.
Konstanz:
IBH-Lab KMUdigital.
pp. 47-61.
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Meierhofer, Jürg; West, Shaun,
2019.
Service value creation using a digital twin[paper].
In:
Naples Forum on Service, Service Dominant Logic, Network & Systems Theory and Service Science: Integrating Three Perspectives for a New Service Agenda, Ischia, Italy, 4-7 June 2019.
Available from: http://www.naplesforumonservice.it/uploads/files/2018/Proceedings/NFS2019-Meierhofer-est.pdf
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Meierhofer, Jürg; Berliat, Roger,
2019.
ServiceToday.
33(4), pp. 96-97.
Available from: https://doi.org/10.21256/zhaw-18545
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Dettling, Marcel; Ruckstuhl, Andreas,
2019.
In:
Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, eds.,
Applied data science : lessons learned for the data-driven business.
Cham:
Springer.
pp. 181-203.
Available from: https://doi.org/10.1007/978-3-030-11821-1_11