Prof. Dr. Jasmina Bogojeska

Work at ZHAW

Position

• Professor for AI and Machine Learning
• Head of Explainable AI Group
• AI Scientist

Focus

Machine learning, Deep learning, Trustworthy/Explainable AI, Multimodal AI, Healthcare (Disease Bioinformatics), Natural Language Processing

Teaching

• Lecturer in the bachelor programmes computer science and data science and on the master and PhD level
• BsC Module Machine Learning and Data Mining 1 (MLDM1)
• BsC Module Machine Learning and Data Mining 2 (Deep Learning)
• MsC Module Machine Learning

Experience

• Professor and Group Head XAI Group
  ZHAW School of Engineering
  03 / 2024 - today
• Senior Lecturer AI/ML and Head of XAI Group
  ZHAW School of Engineering
  09 / 2022 - 02 / 2024
• Senior Principal Data Scientist
  Roche
  01 / 2022 - 09 / 2022
• Senior Machine Learning Scientist
  IBM Research-Zurich
  01 / 2013 - 12 / 2021
• Postdoctoral Scientist
  Max-Planck Institute for Informatics
  11 / 2011 - 12 / 2012
• Doctoral researcher
  Max-Planck Institute for Informatics
  07 / 2007 - 10 / 2011

Education and Continuing education

Education

• Dr. rer. nat (PhD equivalent) / Computer Science
  Max-Planck Institut for Informatics/Saarland University
  07 / 2007 - 10 / 2011
• Masters (MSc) / Computer Science
  Max-Planck Institut for Informatics/Saarland University
  03 / 2005 - 06 / 2007

Continuing Education

CAS Higher and Professional Education
ZHAW School of Management and Law
07 / 2023

Network

Membership of networks

• ZHAW Datalab
• ZHAW Digital Health Lab

ORCID digital identifier

ORCID ID: 0000-0001-5634-7984

Awards

• Edelman Prize Finalist for “IBM Predictive Analytics for Server Incident Reduction in the Wild”
  INFORMS
  07 / 2020
• IBM Research Accomplishment Award for “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

LinkedIn

Projects

• LINA: Shared Large-scale Infrastructure for the Development and Safe Testing of Autonomous Systems / Team member / laufend

Publications

• Deutschmann, Nicolas; Pelissier, Aurelien; Weber, Anna; Gao, Shuaijun; Bogojeska, Jasmina; Rodríguez Martínez, María,

  2024.

  Do domain-specific protein language models outperform general models on immunology-related tasks?.

  Immunoinformatics.

  142667-1190(100036).

  Available from: https://doi.org/10.1016/j.immuno.2024.100036

• Kimmich, Maximilian; Bartezzaghi, Andrea; Bogojeska, Jasmina; Malossi, Christiano; Vu, Ngoc Thang,

  2024.

  Combining data generation and active learning for low-resource question answering [paper].

  In:

  33rd International Conference on Artificial Neural Networks (ICANN), Lugano, Switzerland, 17-20 September 2024.

  Switzerland:

  Springer Nature.

  pp. 131-147.

  Lecture Notes in Computer Science (LNCS) ; 15022.

  Available from: https://doi.org/10.1007/978-3-031-72350-6_9

• Wertz, Lukas; Bogojeska, Jasmina; Mirylenka, Katsiaryna; Kuhn, Jonas,

  2023.

  Reinforced active learning for low-resource, domain-specific, multi-label text classification [paper].

  In:

  Findings of the Association for Computational Linguistics: ACL 2023.

  61st Annual Meeting of the Association for Computational Linguistics (ACL), Toronto, Canada, 9-14 July 2023.

  Stroudsburg, PA:

  Association for Computational Linguistics (ACL).

  Available from: https://doi.org/10.18653/v1/2023.findings-acl.697

• Wertz, Lukas; Bogojeska, Jasmina; Mirylenka, Katsiaryna; Kuhn, Jonas,

  2022.

  Evaluating pre-trained Sentence-BERT with class embeddings in active learning for multi-label text classification [paper].

  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).

  2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP), online, 20-23 November 2022.

  Association for Computational Linguistics.

  pp. 366-372.

  Available from: https://doi.org/10.21256/zhaw-26577

• Zysset, Annina; Feer, Sonja; Saaro, Felix Matthias; Bächli, Mirjam; Niemann, Steffen; Meier, Delphine; Seiler, Michelle; Bogojeska, Jasmina; Dratva, Julia,

  2024.

  Machine learning powered patient records analysis for injury monitoring in children and adolescents.

  In:

  17th European Public Health Conference, Lisbon, Portugal, 12-15 November 2024.

  Oxford University Press.

  pp. iii162.

  Available from: https://doi.org/10.1093/eurpub/ckae144.413

• Feer, Sonja; Zysset, Annina; Saaro, Felix Matthias; Bächli, Mirjam; Niemann, Steffen; Meier, Delphine; Seiler, Michelle; Bogojeska, Jasmina; Dratva, Julia,

  2024.

  Machine learning approach to injury monitoring in children and adolescents.

  In:

  17th European Public Health Conference, Lisbon, Portugal, 12-15 November 2024.

  Oxford University Press.

  pp. iii24.

  Available from: https://doi.org/10.1093/eurpub/ckae144.059

• Feer, Sonja; Zysset, Annina; Bogojeska, Jasmina; Saaro, Felix Matthias; Bächli, Mirjam; Niemann, Steffen; Meier, Delphine; Seiler, Michelle; Dratva, Julia,

  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.

Publications before appointment at the 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.

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