Johannes Jakubik is a Post-Doctoral Researcher within the AI for Climate Impact team at IBM Research in Zurich, Switzerland. At IBM Research, Johannes’ work focuses on pretraining and finetuning geospatial and weather foundation models in collaboration with NASA. His Ph.D. thesis at Karlsruhe Institute of Technology (KIT), Germany, centered around data-centric machine learning and develops a set of scalable methods to enhance data for deep learning. Johannes previously obtained a B.Sc. and M.Sc. from KIT with a focus on machine learning and information systems with research stays at ETH Zurich and internships in industry. Johannes frequently reviews for top conferences (incl. NeurIPS, ECML, AAAI) and top journals (incl. JAIR, Omega), and served as track chair at IEEE IGARSS’23. He has co-published 10+ conference papers (including top conferences like NeurIPS, AAAI, IJCAI) and 5+ journal papers (including top outlets, e.g., Production and Operations Management and the European Journal on Operational Research). Research projects on foundation models in which Johannes is involved have been covered by international media, such as Wall Street Journal and Forbes.