Dragan Stoll
Dragan Stoll
ZHAW
School of Social Work
Institute of Childhood, Youth and Family
Pfingstweidstrasse 96
8037 Zürich
Work at ZHAW
Position
Research associate / PhD Candidate
Focus
Development of machine learning models for text analysis and predictive analytics
Experience
- Research Associate
ZHAW Zurich University of Applied Sciences
09 / 2024 - today - Research Assistance
ZHAW Zurich University of Applied Sciences
09 / 2022 - 08 / 2024 - Data Scientist
Cantonal Office for Youth and Career Services, Canton Zurich
05 / 2013 - 06 / 2022 - Research Associate
Federal Office of Information Technology, Systems and Telecommunication FOITT
09 / 2012 - 04 / 2013 - Research Associate
gfs-zürich Markt- & Sozialforschung
10 / 2000 - 06 / 2012
Education and Continuing education
Education
- lic. phil. / Master of Arts / Political Science, Computer Science
University of Zurich
10 / 2005 - 05 / 2012 - Business Economist HFW / Business Administration
Swiss Institute of Business Administration (SIB)
09 / 2001 - 10 / 2004
Network
ORCID digital identifier
Projects
- Interventions in domestic conflicts involving older people: An analysis of complaints handled by the Independent Complaints Office for Older People (UBA) / Team member / ongoing
- AI for Child Protection: Developing and Evaluating Machine Learning Applications for Decision Support in Child Protection / Project leader / ongoing
- Assessing and improving access to health and social care SErvices for children RENdered vulnerable by Abuse / Team member / ongoing
- Algorithmic fairness in child protection decision-making / Team member / completed
Publications
Articles in scientific journal, peer-reviewed
- Qi, Z., Perron, B. E., Victor, B. G., Stoll, D., & Ryan, J. P. (2026). Small models achieve large language model performance : evaluating reasoning-enabled AI for secure child welfare research. Journal of Evidence-Based Social Work. https://doi.org/10.1080/26408066.2026.2616711
- 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
- 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
Written conference contributions, peer-reviewed
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
Reimer, D., Stoll, D., & Tausendfreund, T. (2025). «Transformation, Transition and Innovation in Child and Youth Care», EuSARF Konferenz im September 2025 in Zagreb. Forum Erziehungshilfen, 31(5), 300–301. https://doi.org/10.3262/FOE2505300
Oral conference contributions and abstracts
- Eicher, N. F., Affolter, K. F., Stoll, D., Lätsch, D., & Tausendfreund, T. (2025, October 7). Impact of the Covid-19 pandemic on child protection services through the lens of administrative data : a systematic review. ISPCAN Congress, Vilnius, Lithuania, 5-9 October 2025.
- 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.
- Eicher, N. F., Affolter, K. F., Stoll, D., Lätsch, D., & Tausendfreund, T. (2025, September 11). A multi-sectoral review of child protection : trends and transitions in administrative data from pre- to post-pandemic. 18th International Conference of the European Scientific Association on Residential & Family Care for Children and Adolescents (EuSARF), Zagreb, Croatia, 8-12 September 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.