Lukas Kondmann

Curriculum Vitae

• Since 10/2019: Research Associate, TUM-SiPEO & Munich School for Data Science (MuDS)
• 01/2022 - 03/2022: Research Fellow, United Nations World Food Programme (WFP)
• 09/2018 - 08/2019: MSc. Social Data Science, University of Oxford 
• 10/2017 - 11/2020: MSc. Quantitative Economics (MQE), Ludwig-Maximilians-Universität Munich (LMU)
• 01/2017 - 05/2017: Visiting Researcher, University of California, Berkeley 
• 08/2015 - 05/2017: Honours Degree in Technology Management, Center for Digital Technology & Management (CDTM)
• 10/2013 - 09/2016: BSc. Economics, Ludwig-Maximilians-Universität Munich 

 Research Interests

• Computer Vision 
• Image Sequence Analysis
• Change and Anomaly Detection 
• Machine Learning for the Developing World 

Key Publications

• Toker, A.*, Kondmann, L.*,  ... & Leal-Taixé, L (2022). DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
• Kondmann, L., Toker, A., ... & Zhu, X. X. (2021). DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space. In Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track.
• Kondmann, L., Toker, A., Saha, S., Schölkopf, B., Leal-Taixé, L., & Zhu, X. X. (2021). Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. IEEE Transactions on Geoscience and Remote Sensing (IEEE TGRS)