Dr. Martin Sterchi
Dr. Martin Sterchi
Tätigkeiten an der FHNW
Dozent, Institute for Competitiveness and Communication
Martin Sterchi ist Dozent für Wirtschaftsstatistik an der Hochschule für Wirtschaft (FHNW). Er studierte an den Universitäten Fribourg (Abschluss 2012) und Zürich (Abschluss 2016) Ökonomie und schloss im Februar 2023 seine Dissertation (Dr. sc.) an der Universität Zürich ab. Der Titel seiner Dissertation lautet "Computational Approaches to Epidemic Prevention on Contact Networks". Er beschäftigt sich schwerpunktmässig mit Methoden der Ökonometrie, Netzwerkanalysen und des Machine Learnings.
Lehre
- Empirische Methoden und Business Analytics (BSc Betriebsökonomie)
- Projektwoche Applied Data Science (BSc Betriebsökonomie, BSc International Management)
- Machine Learning (Vertiefung Managerial Data Science)
- Business Analytics and Quantitative Methods (MSc Business Information Systems)
Beratung
- Tarifierung von Gesundheitsdienstleistungen
- Datenanalysen im Gesundheitssektor
- Ökonomische Analysen in der Landwirtschaft
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Keine peer-reviewed Inhalte verfügbar
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Peer-reviewedSterchi, M., Hilfiker, L., Grütter, R., & Bernstein, A. (2023). Active querying approach to epidemic source detection on contact networks. Scientific Reports, 13(11363). https://doi.org/10.1038/s41598-023-38282-8
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Fuduric, N., Kraft, C., & Sterchi, M. (2021). MeteoSwiss CHAPo: pollen information needs analysis. Fachhochschule Nordwestschweiz FHNW. https://irf.fhnw.ch/handle/11654/42941
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Peer-reviewedSterchi, M., Sarasua, C., Grütter, R., & Bernstein, A. (2021). Outbreak detection for temporal contact data. Applied Network Science, 6(17). https://doi.org/10.1007/s41109-021-00360-z
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Peer-reviewedSterchi, M., Sarasua, C., Grütter, R., & Bernstein, A. (2020). Maximizing the likelihood of detecting outbreaks in temporal networks. In H. Cherifi, S. Gaito, J. F. Mendes, E. Moro, & L. M. Rocha (Eds.), Complex networks and their applications VIII. Volume 2 proceedings of the eighth international conference on complex networks and their applications. Complex Networks 2019 (pp. 481–493). Springer. https://doi.org/10.1007/978-3-030-36683-4_39
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Peer-reviewedStöckli, S., Messner, C., Sterchi, M., & Dorn, M. (2019). Unreliable is better: theoretical and practical impulses for performance management. Die Unternehmung, 73(2), 167–180. https://doi.org/10.5771/0042-059X-2019-2-167
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Peer-reviewedSterchi, M., Faverjon, C., Sarasua, C., Vargas, M. E., Berezowski, J., Bernstein, A., Grütter, R., & Nathues, H. (2019). The pig transport network in Switzerland. Structure, patterns, and implications for the transmission of infectious diseases between animal holdings. Plos One, 14(5), 1–20. https://doi.org/10.1371/journal.pone.0217974
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Peer-reviewedFaverjon, C., Bernstein, A., Grütter, R., Nathues, C., Nathues, H., Sarasua, C., Sterchi, M., Vargas, M. E., & Berezowski, J. (2019). A transdisciplinary approach supporting the implementation of a big data project in livestock production: an example from the Swiss pig production industry. Frontiers in Veterinary Science, 6(215). https://doi.org/10.3389/fvets.2019.00215
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Peer-reviewedHulliger, B., & Sterchi, M. (2018). A survey-based design of a pricing system for psychotherapy. Health Economics Review, 8(29). https://doi.org/10.1186/s13561-018-0213-7
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Keine peer-reviewed Inhalte verfügbar
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Robust methods for survey research
1.1.2018–31.5.2019, Hulliger. BeatClassical robust statistics provides methods for dealing with outliers and these methods are now implemented in many software packages such as SAS and R. Complex surveys pose special problems that cannot be dealt with by the classical approach. Progr...
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Keine peer-reviewed Inhalte verfügbar
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Peer-reviewedHilfiker, L., & Sterchi, M. (2021). Covid-19 superspreading. lessons from simulations on an empirical contact network. 10th International Conference on Complex Networks and their Applications. https://irf.fhnw.ch/handle/11654/43156
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Peer-reviewedSterchi, M. (2018). Pig data. Transdisciplinary approach for health analytics of the Swiss Swine Industry. InnovSur. INNOVATION in Health Surveillance International Forum. https://irf.fhnw.ch/handle/11654/42302
Kontakt
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Dr. Martin Sterchi
- Dozent, Institute for Competitiveness and Communication
- Telefonnummer
- +41 62 957 24 18 (Direkt)
- bWFydGluLnN0ZXJjaGlAZmhudy5jaA==
- Fachhochschule Nordwestschweiz FHNW
Hochschule für Wirtschaft
Riggenbachstrasse 16
4600 Olten
Hochschule für Wirtschaft FHNW, Olten
- Telefon
- +41 84 882 10 11
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