Prof. Dr. Jasmina Bogojeska
Prof. Dr. Jasmina Bogojeska
ZHAW
School of Engineering
Explainable Artificial Intelligence Group
Technikumstrasse 71
8400 Winterthur
Arbeit an der ZHAW
Tätigkeit
- Professorin für künstliche Intelligenz und maschinelles Lernen
- Leiterin Forschungsgruppe Explainable AI
- KI Wissenschaftlerin
Arbeits- und Forschungsschwerpunkte
Maschinelles Lernen, Deep learning, (erklärbare) künstliche Intelligenz (KI), Multimodal KI, Bioinformatik/Gesundheitswesen, Natural Language Processing (NLP)
Lehrtätigkeit
- Dozent in den Bachelor-Studiengängen Informatik und Data Science und auf Stufe Master und Doktorat
- BsC Modul Machine Learning and Data Mining 1 (MLDM1)
- BsC Modul Machine Learning and Data Mining 2 (Deep Learning)
- MsC Modul Machine Learning
Lehrtätigkeit in der Weiterbildung
- CAS Advanced Machine Learning and Machine Learning Operations
- CAS Safe and Secure AI – Standards, Methods and Best Practices
Berufserfahrung
- Professorin und Gruppenleiterin XAI
ZHAW School of Engineering
03 / 2024 - heute - Dozentin KI/ML und Gruppenleiterin XAI
ZHAW School of Engineering
09 / 2022 - 02 / 2024 - Senior Principal Data Scientist
Roche
01 / 2022 - 09 / 2022 - Wissenschaftlerin Maschinelles Lernen
IBM Forschungslabor-Zürich
01 / 2013 - 12 / 2021 - Wissenschaftlerin (Postdoc)
Max-Planck Institut für Informatik
11 / 2011 - 12 / 2012 - Wissenschaftlerin (Promotion)
Max-Planck Institut für Informatik
07 / 2007 - 10 / 2011
Aus- und Weiterbildung
Ausbildung
- Dr. rer. nat. / Informatik
Max-Planck Institut für Informatik/Universität des Saarlandes
07 / 2007 - 10 / 2011 - Master / Informatik
Max-Planck Institut für Informatik/Universität des Saarlandes
03 / 2005 - 06 / 2007
Weiterbildung
CAS Hochschuldidaktik und Erwachsenenbildung
ZHAW School of Management and Law
07 / 2023
Netzwerk
Mitglied in Netzwerken
ORCID digital identifier
Auszeichnungen
- Edelman Prize Finalistin für “IBM Predictive Analytics for Server Incident Reduction in the Wild”
INFORMS
07 / 2020 - IBM Research Accomplishment Award für “IBM Services Solution Advisor and Cognitive Document Risk Analyzer”
IBM
12 / 2019 - IBM Corporate Award for “Predictive Analytics for Server Incident Reduction (PASIR)”
IBM
12 / 2017 - Best Paper Award
CNSM
04 / 2013
Social Media
Projekte
- Erklärbare und handlungsorientierte KI für Intrusion-Detection-Systeme / Projektleiter:in / laufend
- Explainable Multimodal AI for Enhanced Diagnosis of Multiple Chronic Diseases / Projektleiter:in / laufend
- Antibiotika-Resistenz Tracker / Projektleiter:in / laufend
- Zuverlässige domänenspezifische Datenexploration und -analyse durch konversationelle KI / Projektleiter:in / laufend
- LINA: Shared Large-scale Infrastructure for the Development and Safe Testing of Autonomous Systems / Teammitglied / laufend
- Erklärbare KI für Intrusion-Detection-Systeme / Projektleiter:in / abgeschlossen
- Entwicklung eines Machine-Learning Programms für ein Monitoring von Kinder- und Jugendunfällen / Teammitglied / abgeschlossen
Publikationen
Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed
- Bolck, H. et al. (2026) 'LINA's testing infrastructure enables AI to take-off in unmanned aerial vehicles (UAVs)', Frontiers in Robotics and AI, 13(1764248). doi: 10.3389/frobt.2026.1764248.
- Sîrbu, I. et al. (2025) 'GIT-CXR : end-to-end transformer for chest X-ray report generation', Information, 16(7), p. 524. doi: 10.3390/info16070524.
- Deutschmann, N. et al. (2024) 'Do domain-specific protein language models outperform general models on immunology-related tasks?', Immunoinformatics, 142667-1190(100036). doi: 10.1016/j.immuno.2024.100036.
Schriftliche Konferenzbeiträge, peer-reviewed
- Amer-Yahia, S. et al. (2025) 'Towards reliable conversational data analytics', in Proceedings of EDBT 2025. Open Proceedings, pp. 962–969. doi: 10.48786/edbt.2025.78.
- Kimmich, M. et al. (2024) 'Combining data generation and active learning for low-resource question answering', in 33rd International Conference on Artificial Neural Networks (ICANN), Lugano, Switzerland, 17-20 September 2024. Switzerland: Springer, pp. 131–147. doi: 10.1007/978-3-031-72350-6_9.
- Burger, M. et al. (2024) 'Towards large-scale clinical multi-variate time-series datasets', in NeurIPS Workshop on Time Series in the Age of Large Models. OpenReview. doi: 10.21256/zhaw-32746.
- Burger, M. et al. (2024) 'Towards foundation models for critical care time series', in AIM-FM: Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond (AIM-FM Workshop @ NeurIPS′24), Vancouver, Canada, 14 December 2024. arXiv. doi: 10.48550/arXiv.2411.16346.
- Wertz, L. et al. (2023) 'Reinforced active learning for low-resource, domain-specific, multi-label text classification', in Findings of the Association for Computational Linguistics: ACL 2023. Stroudsburg, PA: Association for Computational Linguistics. doi: 10.18653/v1/2023.findings-acl.697.
- Wertz, L. et al. (2022) 'Evaluating pre-trained Sentence-BERT with class embeddings in active learning for multi-label text classification', in Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). Association for Computational Linguistics, pp. 366–372. doi: 10.21256/zhaw-26577.
Mündliche Konferenzbeiträge und Abstracts
- Zysset, A. et al. (2024) 'Machine learning powered patient records analysis for injury monitoring in children and adolescents', in European Journal of Public Health. Oxford University Press, p. iii162. doi: 10.1093/eurpub/ckae144.413.
- Feer, S. et al. (2024) 'Machine learning approach to injury monitoring in children and adolescents', in European Journal of Public Health. Oxford University Press, p. iii24. doi: 10.1093/eurpub/ckae144.059.
- Feer, S. et al. (2024) 'Machine learning powered patient records analysis for injury monitoring in children and adolescents', in Swiss Public Health Conference, Fribourg, Switzerland, 3-4 September 2024.
Publikationen vor Tätigkeit an der ZHAW
- Lukas Fromme, Jasmina Bogojeska, Jonas Kuhn. ContextGen: Targeted Data Generation for Low Resource Domain Specific Text Classification. Proceedings of the 25th International Conference on Artificial Intelligense and Statistics (AISTATS) 2022.
- Mattia Atzeni, Jasmina Bogojeska, Andreas Loukas. SQALER: Scaling Question Answering by Decoupling Mulit-Hop and Logical Reasoning. Advances in Neural Information Processing Systems (NIPS) 2021.
- Jasmina Bogojeska, David Lanyi, Mirela Botezatu, Dorothea Wiesmann. ezNL2SQL: A System for Network Devices Management with a Natural Language Interface for Databases. IFIP/IEEE International Symposium on Integrated Network Management (IM) 2021.
- Jasmina Bogojeska, Ioana Giurgiu, George Stark, Dorothea Wiesmann. IBM Predictive Analytics Reduces Server Downtime. INFORMS Journal on Applied Analytics 2021.
- Chenjie Wan, Nadine Bachmann, Venelin Mitov, François Blanquart, Susana Posada, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Jaques Fellay, Volker Roth, Jürg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Alexandra Calmy, Pietro Vernazza, Enos Bernasconi, Matthias Cavassini, Karin J. Metzner, Huldrych F. Günthard, Roger D. Kouyos and the SHCS. Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART. Nature Communications 2020.
- Christian W Thorball, Alessandro Borghesi, Nadine Bachmann, Chantal Von Siebenthal, Valentina Vongrad, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Volker Roth, Yik Lim Kok, Sonali Parbhoo, Mario Wieser, Jürg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Patrick Schmid, Enos Bernasconi, Matthias Cavassini, Roger D Kouyos, Huldrych F Günthard, Karin J Metzner, Jacques Fellay, and the SHCS. Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment. JAIDS 2020.
- Jan A. Roth, Gorjan Radevski, Catia Marzolini, Andri Rauch, Huldrych F. Günthard, Roger D. Kouyos, Christoph A. Fux, Alexandra U. Scherrer, Alexandra Calmy, Matthias Cavassini, Christian R. Kahlert, Enos Bernasconi, Jasmina Bogojeska, Manuel Battegay and SHCS. Cohort-derived machine learning models for individual prediction of chronic kidney disease in people living with HIV: a prospective multicentre cohort study. The Journal of Infectious Diseases (JID) 2020.
- Nadine Bachmann, Chantal von Siebenthal, Valentina Vongrad, Teja Turk, Kathrin Neumann, Niko Beerenwinkel, Jasmina Bogojeska, Jacques Fellay, Volker Roth, Yik Lim Kok, Christian W Thorball, Alessandro Borghesi, Sonali Parbhoo, Mario Wieser, Jürg Böni, Matthieu Perreau, Thomas Klimkait, Sabine Yerly, Manuel Battegay, Andri Rauch, Matthias Hoffmann, Enos Bernasconi, Matthias Cavassini, Roger D Kouyos, Karin J Metzner, Huldrych Günthard. Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART. Nature Communications 2019.
- Jasmina Bogojeska, Dorothea Wiseman. Transfer Learning for Server Behavior Classification in Small IT Environments. NOMS 2018.
- Ioana Giurgiu, Dorothea Wiesmann, Jasmina Bogojeska, David Lanyi, George Stark, Rodney Wallae, Marcelo Pereira, Alexander Hidalgo. On Adoptation and Impact of Predictive Analytics for Server Incident Reduction. IBM Journal of Research and Development 2017.
- Sonali Parbhoo, Jasmina Bogojeska, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez. Combining Kernel and Model Based Learning for HIV Therapy Selection. AMIA 2017.
- Mirela Botezatu, Ioana Giurgiu, Jasmina Bogojeska, Dorothea Wiseman. Predicting Disk Replacement towards Reliable Data Centers. SIGKDD 2016.
- Mirela Botezatu, Jasmina Bogojeska, Ioana Giurgiu, Hagen Volzer, Dorothea Wiseman. Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching. SIGKDD 2015.
- Andrii Maksai, Jasmina Bogojeska, Dorothea Wiseman. Hierarchical Incident Ticket Classification with Minimal Supervision. ICDM 2014.
- Johannes Schneider, Jasmina Bogojeska, Michail Vlachos. Solving Linear SVMs with Multiple 1D Projections. CIKM 2014.
- Jasmina Bogojeska, Ioana Giurgiu, David Lanyi, George Stark, Dorothea Wiseman. Impact of HW and OS Type and Currency on Server Availability Derived from Problem ticket Analysis. NOMS 2014.
- Ioana Giurgiu, Jasmina Bogojeska, Sergii Nikolaiev, George Stark, Dorothea Wiseman. Analysis of Labor Efforts and their Impact Factors to Solve Server Incidents in Datacenters. CCGRID 2014.
- Jasmina Bogojeska, David Lanyi, Ioana Giurgiu, George Stark, Dorothea Wiseman. Classifying Server Behavior and Predicting Impact of Modernization Actions. CNSM 2013.
- Jasmina Bogojeska, Daniel Stöckel, Maurizio Zazzi, Kaiser Rolf, Incardona Francesca, Rosen-Zvi Michal, Thomas Lengauer. History-alignment models for bias-aware prediction of virological response to HIV combination therapy. AISTATS 2012.
- Jasmina Bogojeska, Thomas Lengauer. Hierarchical Bayes model for predicting outcomes of HIV combination therapies. SAGMB 2012.
- Jasmina Bogojeska. History distribution matching method for predicting effectiveness of HIV combination therapies. NIPS 2011.
- Hiroto Saigo, Andre Altmann, Jasmina Bogojeska, Fabian Müller, Sebastian Nowozin, Thomas Lengauer. Learning from past treatments and their outcome improves prediction of in vivo response to anti-HIV therapy. Statistical Applications in Genetics and Molecular Biology 2011.
- Jasmina Bogojeska, Steffen Bickel, André Altmann, Thomas Lengauer. Dealing with sparse data in predicting outcomes of HIV combination therapies. Bioinformatics 2010.
- Jasmina Bogojeska, Adrian Alexa, André Altmann, Thomas Lengauer, Jörg Rahnenführer. Rtreemix: an R package for estimating evolutionary pathways and genetic progression scores. Bioinformatics 2008.
- Steffen Bickel, Jasmina Bogojeska, Thomas Lengauer, Tobias Scheffer. Multi-Task Learning for HIV Therapy Screening. Proceedings of the International Conference on Machine Learning (ICML) 2008.
- Jasmina Bogojeska, Thomas Lengauer, Jörg Rahnenführer. Stability analysis of mixtures of mutagenetic trees. BMC Bioinformatics 2008.