Dr. rer. nat. Conrad M Albrecht

Tel: +49-(0) 8153 28-1861
Room:  DLR-EOC 2001
E-mail:

conrad.albrecht@{tum,dlr}.de

More information:  

I am research staff @ Zhu lab and PI of "Large-Scale Data Mining in Earth Observation". For 6 years I have been research scientist in the Physical Sciences department at the IBM T.J. Watson Research Center, NY, USA. I graduated in physics with an extra certification in computer science and received a corresponding Ph.D. degree from Heidelberg University, Germany back in 2014. In my Ph.D. thesis I employed distributed computing to study physics at low temperatures.

Broadly speaking, my research interconnects physical modeling and numerical analysis. Specifically, my work contributes to:

  1. Machine learning and numerical optimization to advance artificial intelligence for spatio-temporal data
  2. Development of scalable algorithms and compute pipelines for scientific big data analytics
  3. Remote sensing archeology, and contribution to open-source software.

I am home in Europe and the US. My work intends to initiate, foster, and strengthen long-term transatlantic scientific collaboration with academia, the public sector and industry aboard to make a difference for social good. 

 

Curriculum Vitae

  • since 04/2021: PI of Helmholtz Young Investigator Group "Large-Scale Data Mining in Earth Observation" @ German Aerospace Center (DLR), and Zhu lab (https://ai4eo.de) @ TU Munich
  • 2015-2021: research staff member of "Data Intensive Physical Analytics" group for geospatial data science & remote sensing artificial intelligence @ IBM TJ Watson Research Center, Yorktown Heights, NY, USA ( https://researcher.watson.ibm.com/researcher/view.php?person=us-cmalbrec )
  • 2014: research associate @ the Institute for Theoretical Physics, Heidelberg University
  • 2010-2013: PhD advancing numerical analytics for quantum statistical physics with Prof. Christof Wetterich @ the Heidelberg Graduate School for Fundamental Physics, Heidelberg University
  • 08/2010: visiting researcher @ the European Organization for Nuclear Research (CERN), Geneva, Switzerland

Research Interests

Awards

  • 2022-2023: Alexander von Humboldt CONNECT scholarships (https://www.humboldt-foundation.de/bewerben/foerderprogramme/frontiers-of-research-symposia/connect): BRAGFOST (Brazil-Germany) and GAFOE (Germany-USA)
  • 2021: IBM Research Outstanding Technical Achievement Award for significant contributions to IBMs climate-aware applications in the domain of vegetation intelligence (AI) and its representation as a cloud computing service
  • 2016: best paper award for "IBM PAIRS Curated Big Data Service for Accelerated Geospatial Data Analytics and Discovery" at IEEE BigData 2016, Washington, DC, USA

Key Publications

  • "Urban Forests for Carbon Sequestration and Heat Island Mitigation", L. Klein and C. Albrecht, AI4Good Fragile Earth workshop at 28th ACM SIGKDD Int. Conf. on Knowl. Discov. & Data Min., Washington, DC, USA (2022)
  • "Self-supervised Learning in Remote Sensing: A Review", Y. Wang, C. Albrecht, N. Ait Ali Braham, L. Mou, X. Zhu, accepted in IEEE Trans. Geosci. Remote Sens. (2022)
  • "AutoGeoLabel: Automated Label Generation for Geospatial Machine Learning", C. Albrecht, F. Marianno, L. Klein, IEEE Big Data 2021
  • Patent US10572976B2: "Enhancing Observation Resolution Using Continuous Learning", H. Hamann, S. Pankanti, C. Albrecht, S. Lu (granted Feb 2020) https://patents.google.com/patent/US10572976B2
  • Patent US11210268B2: "Scalable Space-Time Density Data Fusion", C. Albrecht, M. Freitag, H. Hamann (granted Dec 2021) https://patents.google.com/patent/US11204896B2
  • "Map Generation from Large Scale Incomplete and Inaccurate Data Labels", R. Zhang, C. Albrecht, W. Zhang, X. Cui, U. Finkler, D. Kung, S. Lu, Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, virtual event, CA, USA (2020)
  • "Learning and Recognizing Archeological Features from LiDAR Data", C. Albrecht, C. Fisher, M. Freitag, H. Hamann, S. Pankanti, F. Pezzutti, F. Rossi, IEEE Big Data 2019
  • "Scalable Space-Time Density Data Fusion", C. Albrecht, M. Freitag, H. Hamann, worldwide patent application WO2019034999A2 filed 08/2017 ( https://patents.google.com/patent/WO2019034999A2/)
  • "PAIRS: A Scalable Geo-Spatial Data Analytics Platform", L. Klein, F. Marianno, C. Albrecht, M. Freitag, S. Lu, N. Hinds, X. Shao, S. Bermudez, H. Hamann, IEEE Big Data 2015
  • "Induced Delocalization by Correlation and Interaction in the 1D Anderson Model", C. Albrecht, S. Wimberger, Phys. Rev. B 85, 045107 (2012)

Professional Services & Scientific Event Organization

Scientific Collaborations