Dr. Johannes Jakubik


Johannes has been a Ph.D. student at the Applied AI in Services Lab at Karlsruhe Institute of Technology (KIT). He is now serving as a postdoctoral researcher at IBM Research Europe. His research interests include:

  •  Applied deep learning
  •  Foundation models
  •  Data-centric AI
  •  Uncertainty quantification

Curriculum Vitae

Johannes is a postdoctoral researcher within the AI for Climate Impact Team at IBM Research. Throughout his Ph.D., he mainly focused on applied deep learning and data-centric AI and served as a visiting researcher at IBM Research. He has a background in applied machine learning, having worked on a variety of topics at IBM, KIT, and ETH Zurich, and during internships in industry. Currently, his focus is on pretraining and finetuning geospatial foundation models in collaboration with NASA. 

Media and Honors

Research projects in which Johannes is involved have been covered by international media, such as Wall Street Journal, Forbes, Reuters, CNBC, and national media, such as Spektrum der Wissenschaft. Together with a team of co-authors, Johannes has received the best full paper award at HHAI'23 and got nominated for the best full paper award at WI'23. He was part of the keynote on generative AI for business and climate science at IBM Think on Tour together with IBM VP R&D David Faller. Johannes work was selectively funded by scholarships for international research on AI.

Community Service

Johannes frequently reviews for top conferences (incl. NeurIPS, ECML, AAAI) and top journals (incl. JAIR, Omega). He served as track chair at IEEE IGARSS’23.


Johannes has co-published 5+ journal papers (including top outlets, e.g., Production and Operations Management and the European Journal on Operational Research) and 10+ conference papers (including top conferences like NeurIPS, AAAI, ICWSM, and IEEE IGARSS).

Please find a full list of publications Johannes has co-authored on Google Scholar.

PhD Theses
Data-Centric Artificial Intelligence: Foundations and Methods for Deep Learning. PhD dissertation
Jakubik, J.
2024, April 8. Karlsruher Institut für Technologie (KIT)
Journal Articles
Data-Centric Artificial Intelligence
Jakubik, J.; Vössing, M.; Kühl, N.; Walk, J.; Satzger, G.
2024. Business & information systems engineering. doi:10.1007/s12599-024-00857-8
Book Chapters
An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making
Jakubik, J.; Schöffer, J.; Hoge, V.; Vössing, M.; Kühl, N.
2023. Machine Learning and Principles and Practice of Knowledge Discovery in Databases – International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part I. Ed.: I. Koprinska, 353–368, Springer Nature Switzerland. doi:10.1007/978-3-031-23618-1_24
Journal Articles
Sanitizing data for analysis: Designing systems for data understanding
Holstein, J.; Schemmer, M.; Jakubik, J.; Vössing, M.; Satzger, G.
2023. Electronic Markets, 33 (1), Art.-Nr.: 52. doi:10.1007/s12525-023-00677-w
Incorporating financial news for forecasting Bitcoin prices based on long short-term memory networks
Jakubik, J.; Nazemi, A.; Geyer-Schulz, A.; Fabozzi, F. J.
2023. Quantitative Finance, 23 (2), 335–349. doi:10.1080/14697688.2022.2130085
Conference Papers
Toward Foundation Models for Earth Monitoring: Generalizable Deep Learning Models for Natural Hazard Segmentation
Jakubik, J.; Muszynski, M.; Vössing, M.; Kühl, N.; Brunschwiler, T.
2023. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023), 5638–5641, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS52108.2023.10282643
What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation
Blumenstiel, B.; Jakubik, J.; Kühne, H.; Vössing, M.
2023. 37th Conference on Neural Information Processing Systems (NeurIPS 2023). doi:10.48550/arXiv.2306.15521
Online Emotions during the Storming of the U.S. Capitol : Evidence from the Social Media Network Parler
Jakubik, J.; Vössing, M.; Pröllochs, N.; Bär, D.; Feuerriegel, S.
2023. Proceedings of the 17th International AAAI Conference on Web and Social Media (ICWSM), Limassol, CY, June 5-8, 2023. Ed.: Y.-R. Lin, Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/icwsm.v17i1.22157
On the Interdependence of Reliance Behavior and Accuracy in AI-Assisted Decision-Making
Schoeffer, J.; Jakubik, J.; Voessing, M.; Kuehl, N.; Satzger, G.
2023. HHAI 2023: Augmenting Human Intellect – Proceedings of the Second International Conference on Hybrid Human-Artificial Intelligence. Ed.: P. Lukowicz, IOS Press. doi:10.3233/FAIA230074
Improving the Efficiency of Human-in-the-Loop Systems: Adding Artificial to Human Experts
Jakubik, J.; Weber, D.; Hemmer, P.; Vössing, M.; Satzger, G.
2023. Proceedings of the International Conference on Wirtschaftsinformatik, 18th - 21st Sept 2023, Paderborn
Learning to Defer with Limited Expert Predictions
Hemmer, P.; Thede, L.; Vössing, M.; Jakubik, J.; Kühl, N.
2023. Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, February 7-14, 2023
Journal Articles
Data‐driven allocation of development aid towards Sustainable Development Goals: Evidence from HIV/AIDS
Jakubik, J.; Feuerriegel, S.
2022. Production and Operations Management, 31 (6), 2739–2756. doi:10.1111/poms.13714
Conference Papers
Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts
Hemmer, P.; Schellhammer, S.; Vössing, M.; Jakubik, J.; Satzger, G.
2022. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2478–2484, International Joint Conferences on Artificial Intelligence Organization (IJCAI). doi:10.24963/ijcai.2022/344
An Empirical Evaluation of Estimated Outcomes as Explanations in Human-AI Decision-Making
Jakubik, J.; Schöffer, J.; Hoge, V.; Vössing, M.; Kühl, N.
2022. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Instance Selection Mechanisms for Human-in-the-Loop Systems in Few-Shot Learning
Jakubik, J.; Blumenstiel, B.; Vössing, M.; Hemmer, P.
2022. Wirtschaftsinformatik 2022 : Proceedings. Bd.: 6, AIS eLibrary (AISeL)
Designing a Human-in-the-Loop System for Object Detection in Floor Plans
Jakubik, J.; Hemmer, P.; Vössing, M.; Blumenstiel, B.; Bartos, A.; Mohr, K.
2022. Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI 2022), Online, 22.02.2022-01.03.2022, 12524–12530, Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v36i11.21522
Journal Articles
Directed particle swarm optimization with Gaussian-process-based function forecasting
Jakubik, J.; Binding, A.; Feuerriegel, S.
2021. European journal of operational research, 295 (1), 157–169. doi:10.1016/j.ejor.2021.02.053
Journal Articles
Reinforcement learning for opportunistic maintenance optimization
Kuhnle, A.; Jakubik, J.; Lanza, G.
2019. Production Engineering, 13 (1), 33–41. doi:10.1007/s11740-018-0855-7