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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Hertweck, Corinna; Heitz, Christoph; Loi, Michele,
2021.
On the moral justification of statistical parity[paper].
In:
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency.
4th ACM Conference on Fairness, Accountability, and Transparency (FAccT), online, 3-10 March 2021.
New York:
Association for Computing Machinery.
pp. 747-757.
Available from: https://doi.org/10.1145/3442188.3445936
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2021.
Schnell reagierende Planungsalgorithmen für die Kundenauftragsproduktion[poster].
In:
6. F&E-Konferenz zu Industrie 4.0, Online, 3. Februar 2021.
Available from: https://www.industrie2025.ch/fileadmin/industrie2025/5_Veranstaltungen/F_E-Konferenz_2021/Praesentationen_fuer_Download/05_Thomas_Herrmann.pdf
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Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,
2021.
Deep learning for fault detection : the path to predictive maintenance of wind turbines[paper].
In:
Sammelband zu den 6. Energieforschungsgesprächen Disentis.
Energieforschungsgespräche Disentis 2021, online, 20.-22. Januar 2021.
Disentis:
Stiftung Alpines Energieforschungscenter AlpEnForCe.
pp. 24-26.
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Fahrner, Matthias; Kook, Lucas; Fröhlich, Klemens; Biniossek, Martin L.; Schilling, Oliver,
2021.
Proteomes.
9(2), pp. 26.
Available from: https://doi.org/10.3390/proteomes9020026
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Templ, Matthias,
2021.
Artificial neural networks to impute rounded zeros in compositional data.
In:
Filzmoser, Peter; Hron, Karel; Martín-Fernández, Josep Antoni; Palarea-Albaladejo, Javier, eds.,
Advances in Compositional Data Analysis : Festschrift in Honour of Vera Pawlowsky-Glahn.
Cham:
Springer.
pp. 163-187.
Available from: https://doi.org/10.1007/978-3-030-71175-7_9