Lukas Kondmann

Room:  2102 (DLR-EOC)
E-mail: lukas.kondmann[at]dlr.de 

 

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: MScSocial 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)