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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Grize, Yves-Laurent; Fischer, Wolfram; Lützelschwab, Christian,
2020.
Machine learning applications in nonlife insurance.
Applied Stochastic Models in Business and Industry.
36(4), pp. 523-537.
Available from: https://doi.org/10.1002/asmb.2543
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Grize, Yves-Laurent; Fischer, Wolfram; Lützelschwab, Christian,
2020.
Machine learning applications in non‐life insurance : discussion rejoinder.
Applied Stochastic Models in Business and Industry.
36(4), pp. 545-547.
Available from: https://doi.org/10.1002/asmb.2564
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Templ, Matthias,
2020.
Modeling and prediction of the impact factor of journals using open-access databases.
Austrian Journal of Statistics.
49(5), pp. 35-58.
Available from: https://doi.org/10.17713/ajs.v49i5.1186
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Bütikofer, Stephan; Steiner, Albert; Wüst, Raimond,
2020.
Periodic timetabling with flexibility based on a mesoscopic topology[paper].
In:
Operations Research Proceedings 2019.
Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, 4-6 September 2019.
Cham:
Springer.
pp. 789-795.
Operations Research Proceedings.
Available from: https://doi.org/10.1007/978-3-030-48439-2_96
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Rosadi, Dedi; Setiawan, Ezra Putranda; Templ, Matthias; Filzmoser, Peter,
2020.
Robust covariance estimators for mean-variance portfolio optimization with transaction lots.
Operations Research Perspectives.
7(100154).
Available from: https://doi.org/10.1016/j.orp.2020.100154