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:
- Machine learning and numerical optimization to advance artificial intelligence for spatio-temporal data
- Development of scalable algorithms and compute pipelines for scientific big data analytics
- 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 visiting scientist at SiPEO @ 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
- machine learning and numerical optimization to advance artificial intelligence for spatio-temporal data
- development of scalable algorithms and compute pipelines for scientific big data analytics
- remote sensing archeology (https://www.youtube.com/watch?v=Ce3g6vnfSiw), and contribution to open source software (https://github.com/ibm/ibmpairs)
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
- Member of the Bavarian American Academy (https://www.amerikahaus.de/en/academy/)
- Scientific associate with HelmholtzAI (https://www.helmholtz.ai/)
- Reviewer of journals "Remote Sensing of Environment" (https://www.sciencedirect.com/journal/remote-sensing-of-environment) and "IEEE Transactions on Geoscience & Remote Sensing" (https://www.grss-ieee.org/publications/transactions-on-geoscience-remote-sensing/), IEEE BigData conferences (https://bigdataieee.org/), and "Climate Informatics" workshop series (http://www.climateinformatics.org/), "Machine Learning for Physical Sciences" workshop series https://ml4physicalsciences.github.io of the 2021 & 2022 NeurIPS conference, 2023 ICML "Synergy of Scientific and Machine Learning Modeling" workshop (https://syns-ml.github.io/2023), 2023 NeurIPS "Datasets and Benchmarks" track
- Committee member for the admission of scholars to the "Studienstiftung des Deutschen Volkes" (https://www.studienstiftung.de/)
- Mentor for The City Tutors (http://www.thecitytutors.com/)
- 2022: workshop co-organizer of IEEE BigData 2022 workshop "Digital Twins for Accelerated Discovery of Climate & Sustainability" https://sites.google.com/view/bigdata-adocs/organizers
- 2022: consultant for LEAM:AI (https://leam.ai) initiative of the German AI Association on the authority of the Federal Ministry for Economic Affairs and Climate Action (BMWK)
- Member of the Open Geospatial Consortium (OGC), https://www.ogc.org
- 2021: referee of scientific proposal for the U.S. Department of Agriculture
- 2020: workshop organizer of AAAS meeting symposium "Geospatial Insights for a sustainable Environment" (https://aaas.confex.com/aaas/2020/meetingapp.cgi/Session/23997)
- 2018-2019: mentor for IBM interns from Cornell University (https://cornelldata.science/)
- 2017: keynote @ 8th ACM SIGSPATIAL (http://cse.ucdenver.edu/~IWGS2017/keynote.html)
Scientific Collaborations
- IBM TJ Watson Research Center, NY, USA: https://research.ibm.com/labs/watson
- Institute of Nasca, Yamagata University, Japan: https://www-hs.yamagata-u.ac.jp/en/institute/nasca
- Juelich Supercomputing Center, Germany: https://www.fz-juelich.de/profile/kesselheim_s
- Intelligent Computing lab, Yale University, USA: https://intelligentcomputinglab.yale.edu
- THOTH lab, INRIA Grenoble, France: https://team.inria.fr/thoth
- Education team @ Deutsches Museum, Germany: https://www.deutsches-museum.de/museumsinsel/programm/bildungsangebote/schulen
- Hydrology Section, GFZ German Research Centre for Geosciences, Germany: https://www.gfz-potsdam.de/en/section/hydrology/overview
- "EvoLand" EU Horizon Europe Consortium: https://www.evo-land.eu/about-evoland/#partners