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
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Team IDP
Publikationen
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Füchslin, Rudolf Marcel; Ambühl, Jacques; Faggian, Alessia; Fellermann, Harold M.; Flumini, Dandolo; Geller, Armando; Hanczyc, Martin M.; Klinkert, Andreas; Krütli, Pius; Matuttis, Hans-Georg; Ott, Thomas; Scheidegger, Stephan; Schmid, Gary Bruno; Smieszek, Timo; Schneider, Johannes J.; Steiner, Albert; Weyland, Mathias S.,
2023.
Ethical aspects of computational modelling in science, decision support and communication[paper].
In:
Artificial Life and Evolutionary Computation.
XV Italian Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021.
Cham:
Springer.
Communications in Computer and Information Science ; 1722.
Available from: https://doi.org/10.1007/978-3-031-23929-8_24
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Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Ziebart, Volker; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K.O.; Heitmann, Björn; Wilhelm, Dirk,
2023.
Deconvolution of NMR spectra : a deep learning-based approach[poster].
In:
Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-27429
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Bürgin, Reto; Muratori, Corrado; Roca-Riu, Mireia; Heitz, Christoph,
2023.
A space-time model for demand in free-floating carsharing systems.
Journal of Advanced Transportation.
2023(6610624).
Available from: https://doi.org/10.1155/2023/6610624
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Wulf, Jochen; Brenner, Walter,
2023.
Bereit für den digitalen Endkunden? : ein Fähigkeitsmodell.
In:
Gassmann, Oliver; Sutter, Philipp, eds.,
Digitale Transformation gestalten.
Hanser.
pp. 207-222.
Available from: https://doi.org/10.3139/9783446468887.012
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Scherrer, Maike; Steiner, Albert; Rühlin, Viola,
2023.
Greening urban logistics : introducing a method to evaluate optimised decoupling hub locations[paper].
In:
Transportation Research Procedia.
9th Transport Research Arena (TRA), Lisbon, Portugal, 14-17 November 2022.
Elsevier.
pp. 572-579.
Available from: https://doi.org/10.1016/j.trpro.2023.11.441