Together with a range of amazing co-authors, I have published 15+ conference papers (including top conferences like NeurIPS, CVPR, ECML) and 5+ journal papers (including top outlets, e.g., Journal of Artificial Intelligence Research, European Journal on Operational Research). You can find a full list of publications I co-authored also on Google Scholar.
I also contribute to a range of communities as reviewer, associate editor, and track chair including conferences like NeurIPS, AAAI, ECML, and journals like the Journal of Artificial Intelligence Research.
Selected conference papers
NeurIPS
Blumenstiel, B.*, Jakubik, J.*, Kühne, H., Vössing, M. (2023). What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation. NeurIPS 2023. Paper Website Code. * denotes shared first authorship (VHB-2024: A, CORE: A*).
CVPR
Blumenstiel, B., Fraccaro, P., Marsocci, V., Jakubik, J., Maurogiovanni, S., Czerkawski, M., … & Longépé, N. (2025). Terramesh: A planetary mosaic of multimodal earth observation data. In Proceedings of the Computer Vision and Pattern Recognition Conference (pp. 2394-2402). Paper
AAAI
Hemmer, P., Thede, L., Vössing, M., Jakubik, J., & Kühl, N. (2023). Learning to Defer with Limited Expert Predictions. AAAI’23. Paper Code (VHB-2024: A, CORE: A*)
AAAI
Jakubik, J., Hemmer, P., Vössing, M., Blumenstiel, B., Bartos, A., & Mohr, K. (2022, June). Designing a Human-in-the-Loop System for Object Detection in Floor Plans. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 11, pp. 12524-12530). Paper
AAAI
Müller, L., Hemmer, P., Queisner, M., Sauer, I., Allmendinger, S., Jakubik, J., … & Kühl, N. (2024). Redefining the laparoscopic spatial sense: AI-based intra-and postoperative measurement from stereoimages. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 21, pp. 22948-22954). Paper
IJCAI
Hemmer, P., Schellhammer, S., Vössing, M., Jakubik, J., & Satzger, G. Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts. IJCAI’22. Paper Code (VHB-2024: A, CORE: A*)
ECML
Marimo, C. T., Blumenstiel, B., Nitsche, M., Jakubik, J., & Brunschwiler, T. (2025). Beyond the visible: Multispectral vision-language learning for earth observation. Accepted at ECML. Paper
Selected journal publications
Journal of Artificial Intelligence Research
Jakubik, J., Vössing, M., Maskey, M., Wölfle, C., & Satzger, G. (2024). Improving Label Error Detection and Elimination with Uncertainty Quantification. Accepted at JAIR. Paper (CORE: A, IF: 2.4)
Journal of Artificial Intelligence Research
Schoeffer, J., Jakubik, J., Voessing, M., Kuehl, N., & Satzger, G. (2024). AI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventions. Accepted at JAIR. Paper (CORE: A, IF: 2.4)
European Journal of Operational Research
Jakubik, J., Binding, A., & Feuerriegel, S. (2021). Directed particle swarm optimization with Gaussian-process-based function forecasting. European Journal of Operational Research, 295(1), 157-169. Paper (VHB: A, IF: 6.4)
Productions and Operations Management
Jakubik, J., & Feuerriegel, S. (2022). Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS. Production and Operations Management, 31(6), 2739-2756. Paper (FT-50, VHB: A, IF: 4.6)
IEEE Geoscience and Remote Sensing Magazine
Gomes, C., Wittmann, I., Robert, D., Jakubik, J., Reichelt, T., Maurogiovanni, S., … & Albrecht, C. M. (2025). Lossy neural compression for geospatial analytics: A review. IEEE Geoscience and Remote Sensing Magazine.
Business & Information Systems Engineering
Jakubik, J., Vössing, M., Kühl, N., Walk, J., & Satzger, G. (2022). Data-centric Artificial Intelligence. Business & Information Systems Engineering. Paper (VHB: B, IF: 7.9)
Quantitative Finance
Jakubik, J., Nazemi, A., Geyer-Schulz, A., & Fabozzi, F. J. (2023). Incorporating financial news for forecasting Bitcoin prices based on long short-term memory networks. Quantitative Finance, 23(2), 335-349. Paper (VHB: B, IF: 2.0)
Electronic Markets
Holstein, J., Schemmer, M., Jakubik, J., Vössing, M., Satzger, G. (2023). Sanitizing Data for Analysis: Designing Systems for Data Understanding. Electronic Markets, 33 (52). Paper (VHB: B, IF: 8.5)
Supervised students
I had the priviledge to work with outstanding students in the past who have contributed to a range of the above publications that I want to acknowledge in the following:
- Felix Yang – M.Sc. thesis at ETH Zurich/IBM Research (now: Research Engineer at NVIDIA)
- Gianfranco Basile – M.Sc. thesis at ETH Zurich/IBM Research (incoming: PhD student at EPFL)
- Benedikt Blumenstiel – M.Sc. thesis at KIT (now: Research Engineer at IBM Research)
- Isabelle Wittmann – M.Sc. thesis at ETH Zurich, co-supervisor (now: Research Engineer at IBM Research)
- Joshua Holstein – M.Sc. thesis at KIT (now: PhD student at KIT)
- Niklas Kopp – M.Sc. thesis at KIT (now: Client Engineering at IBM)
- Daniel Weber – M.Sc. thesis at KIT (now: Boston Consulting Group)
- Sinan Glagau – M.Sc. thesis at KIT (now: Deloitte Consulting)
- Nicolas Wehrli – B.Sc. thesis at ETH Zurich (now: ETH Zurich)
- Silvan Jödicke – B.Sc. thesis at ETH Zurich (now: ETH Zurich)
- Luca Reutter – B.Sc. thesis at KIT (now: KPMG)