Dr. Samuel Wehrli

Projects

• Deep Learning-Based Real-Time EEG Monitoring for Clinical Interventions / Project leader / ongoing
• Digital Health Zurich: a practice lab for patient-centred clinical innovation / Team member / ongoing
• Predictive chance modelling: Exploration of a new approach to professional decision-making in child protection / Team member / completed
• Machine learning and algorithms in social work / Team member / completed

Publications

Articles in scientific journal, peer-reviewed

• Amacker, J., Veneruso, M., Pereno, M., Ulzega, S., Wehrli, S., Hirsch, S., Nobili, L., Miano, S., Manconi, M., & Castelnovo, A. (2026). Shared local brain dynamics in pediatric and adult NREM parasomnias. Sleep. https://doi.org/10.1093/sleep/zsag123
• Stoll, D., Jud, A., Wehrli, S., Lätsch, D., Steinmann, S., Wallimann, M. S., & Quehenberger, J. (2025). Case reports unlocked : leveraging retrieval-augmented generation with large language models to advance research on psychological child maltreatment. Child Abuse & Neglect, 169(107653). https://doi.org/10.1016/j.chiabu.2025.107653
• Kirchberger, J., Kunz, D., Perrot, G., Hirsch, S., Leifke, M., Hölz, B., Geissmann, L., Käch, M., Wehrli, S., & Eckstein, J. (2025). An explorative study on movement detection using wearable sensors in acute care hospital patients. Scientific Reports, 15(1), 19941. https://doi.org/10.1038/s41598-025-04340-6
• Stoll, D., Wehrli, S., & Lätsch, D. (2024). Case reports unlocked : harnessing large language models to advance research on child maltreatment. Child Abuse & Neglect, 160(107202). https://doi.org/10.1016/j.chiabu.2024.107202
• Reichl, J. J., Leifke, M., Wehrli, S., Kunz, D., Geissmann, L., Broisch, S., Illien, M., Wellauer, D., von Dach, N., Diener, S., Manser, V., Herren, V., Angerer, A., Hirsch, S., Hölz, B., & Eckstein, J. (2024). Pilot study for the development of an automatically generated and wearable-based early warning system for the detection of deterioration of hospitalized patients of an acute care hospital. Archives of Public Health, 82(1), 179. https://doi.org/10.1186/s13690-024-01409-y
• Wehrli, S., Hertweck, C., Amirian, M., Glüge, S., & Stadelmann, T. (2021). Bias, awareness, and ignorance in deep-learning-based face recognition. AI and Ethics, 2(3), 509–522. https://doi.org/10.1007/s43681-021-00108-6

Written conference contributions, peer-reviewed

• Brunschwiler, M., Hollenstein, L., Wehrli, S., & Kunz, D. (2025). Enhancing information extraction for simulation modelling using large language models [Conference paper]. In S. Rank, M. Kühn, & T. Schmidt (Eds.), Simulation in Produktion und Logistik 2025 (pp. 49–41). Technische Universität Dresden. https://doi.org/10.25368/2025.282
• Stoll, D., Jud, A., Wehrli, S., Steinmann, S., Wallimann, M. S., & Quehenberger, J. (2025, September 10). Case reports unlocked : leveraging retrieval-augmented generation with large language models to advance research on child psychological maltreatment. 18th International Conference of the European Scientific Association on Residential & Family Care for Children and Adolescents (EuSARF), Zagreb, Croatia, 8-12 September 2025.

Other publications

• Biberstein, L., Girschik, K., & Wehrli, S. (2024). Twitter-Analysen der Polizei : Erkenntnisse für die Soziale Arbeit. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-29968
• Truninger, D., Zysset, A., Wehrli, S., Albermann, K., von Rhein, M., & Wieber, F. (2022, September 19). Digital pens for measuring fine motor skills in school-aged children with and without ADHD. 4. Digital Health Lab Day, Winterthur, Schweiz, 12. September 2022. https://doi.org/10.21256/zhaw-25701

Oral conference contributions and abstracts

• Stoll, D., Jud, A., Wehrli, S., Wallimann, M. S., Steinmann, S., & Quehenberger, J. (2025, October 6). Case reports unlocked : applying RAG-prompting methods and large language models to advance research on child maltreatment. ISPCAN Congress, Vilnius, Lithuania, 5-9 October 2025.
• Stoll, D., Lätsch, D., & Wehrli, S. (2024, August 21). Applying machine learning text classification methods and large language models for data collection of mentions of child maltreatment. ISPCAN Congress, Uppsala, Sweden, 18-21 August 2024.

Patents and patent applications

• Wehrli, Samuel; Wieber, Frank; Rüffer, Daniel,

  2026.

  System and method for supporting focus of a person.

  Patent number WO2026027258 A1

  (2026-02-05)

  .

  Available from: https://worldwide.espacenet.com/patent/search?q=pn%3DWO2026027258A1

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