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Mitarbeiterbild von Felix Riese

M.Sc. Felix Riese

Wissenschaftlicher Mitarbeiter
room: 002 (Geb. 20.52)
phone: +49 721 608 47304
fax: +49 721 608 48450
felix rieseUle5∂kit edu



Curriculum vitae

Research interests

Teaching

Other profiles

Awards

Workshops, talks and posters

Media

Publications

Projects

 

Curriculum vitae

04/2019 TRUST Measurement Campaign in Peru
09/2018 "Brain to Market" Summer School in Paris about neuropathology and entrepreneurship (aftermovie)
07/2018 VISUM Summer School in Porto (PT) about machine learning and computer vision (aftermovie)
Since 06/2018 Participant of the KIT mentoring program X-Ment for researchers
Since 01/2018 MBA fellow at the Collège des ingénieurs (CDI) in Paris, France
Since 05/2017 PhD student at the Institute for Photogrammetry and Remote Sensing of the Karlsruhe Institute of Technology (KIT)
01/2016 - 05/2018 Lecturer at the Baden-Wuerttemberg Cooperative State University (DHBW) in the degree programm "computer science" (see teaching)
10/2014 - 03/2017 Master of Science in physics at the KIT, major in "data analysis in particle physics"
  Masterthesis: "Boosted-Jet Reconstruction Methods in a Search for Higgs-Boson Production in Association with a Top-Quark-Antiquark Pair at the CMS Experiment" at the Institute of Experimental Nuclear Physics (EKP) of the KIT with Prof. Dr. Husemann
10/2011 - 09/2014 Bachelor of Science in physics at the KIT

 

Research interests

  • Machine Learning: Data Analysis, Supervised and Unsupervised Learning, Self-Organizing Maps (SOM), Deep Learning, Python
  • Hyperspectral Remote Sensing, Multispectral Satellites (Sentinel-2), UAV
  • Geoscience: estimation of soil surface parameters

 

Teaching

  • Introduction to linear algebra, analysis and statistics at the DHBW Karlsruhe
  • Introduction to knowledge-based systems at the DHBW Karlsruhe
  • Introduction to LaTeX at the DHBW Karlsruhe

 

Other profiles

 

Awards

  • Best Paper Award at the ISPRS Geospatial Week 2019 in Enschede (NL)

 

Workshops, talks and posters

June 2019 Talk about the publication "Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data" at the ISPRS Geospatial Week in Enschede (NL), Code
May 2019 Talk "Satellite Computer Vision mit Keras und TensorFlow - Best Practices und Beispiele aus der Forschung" at the M3 conference in Mannheim (DE), Slides and Code
April 2019 2-day Workshop about "Introduction to Artificial Intelligence in Remote Sensing" at the Universidad Nacional Agraria La Molina in Lima (PE)
March 2019 Poster about "Land use classification with remote sensing data and machine learning in the Lima region (Peru)" at the Tag der Hydrologie 2019 (engl. Hydrology Day) in Karlsruhe (DE)
February 2019 Poster about "Land use classification with remote sensing data and machine learning in the Lima region (Peru)" at the GRoW Midterm Conference in Frankfurt am Main (DE)
October 2018 Talk "Satellite data is for everyone: Insights into modern remote sensing research with open data and Python" at the PyCon.DE 2018 in Karlsruhe (DE), Slides and Code and Video of the talk
October 2018 Talk about the publication "Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data" at the ISPRS TCI Symposium 2018 in Karlsruhe (DE)
September 2018 Talk about the publication "Fusion of hyperspectral and ground penetrating radar to estimate soil moisture" at the WHISPERS 2018 conference in Amsterdam (NL)
July 2018 Talk about the publication "Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data" at the IGARSS 2018 conference in Valencia (ES)
July 2018 Poster about "Self-organizing maps for regression with hyperspectral data" at VISUM summer school in Porto (PT)
March 2018 Talk about the publication "Modeling Subsurface Soil Moisture Based on Hyperspectral Data - First Results of a Multilateral Field Campaign" at the DGPF conference in Munich (DE)

 

Media and Press

  • Press release by the KIT SEK with the title "From satellite image towards drinking water concepts" about the Peru measurement campaign and the contribution of the IPF in the TRUST project
  • Youtube video with the title "Artificial Intelligence in Environmental Research" about my PhD and the contribution of the IPF in the TRUST project
  • Podcast episode about "Remote Sensing with Multispectral Remote Sensing" of TechTiefen with Nico Kreiling in July 2019
  • Youtube video of the talk "Satellite data is for everyone: Insights into modern remote sensing research with open data and Python" at PyCon.DE in October 2018

Publikationen


2019
León, C. D.; Kosow, H.; Zahumensky, Y.; Krauß, M.; Wasielewski, S.; Minke, R.; Wienhöfer, J.; Riese, F. M.; Keller, S.; Sturm, S.; Brauer, F.; Hügler, M.; Gottwalt, J.; Riepl, D. (2019). Solutions and planning tools for water supply and wastewater management in prosperous regions tackling water scarcity. Proceedings of the GRoW Midterm Conference - Global analyses and local solutions for sustainable water resources management, Frankfurt am Main, 20-21 February 2019. Ed.: A. Kramer, 28–31, adelphi, Berlin.
Riese, F. M.; Keller, S. (2019). Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019 ISPRS) Geospatial Week 2019, Enschede, NL, June 10-14, 2019. Vol. IV-2/W5, 615–621. doi:10.5194/isprs-annals-IV-2-W5-615-2019
2018
Keller, S.; Maier, P.; Riese, F.; Norra, S.; Holbach, A.; Börsig, N.; Wilhelms, A.; Moldaenke, C.; Zaake, A.; Hinz, S. (2018). Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity. International journal of environmental research and public health, 15 (9), 1881/1–15. doi:10.3390/ijerph15091881
Keller, S.; Riese, F. M.; Allroggen, N.; Jackisch, C.; Hinz, S. (2018). Modeling Subsurface Soil Moisture Based on Hyperspectral Data : First Results of a Multilateral Field Campaign. Photogrammetrie, Fernerkundung, Geoinformatik, Kartographie 2018 (PFGK18) : Beiträge der 37. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 5. Münchner GI-Runde Runder Tisch GIS e.V. und des 66. Deutscher Kartographie Kongress der DGfK e.V., München, Deutschland, 7. - 9. März 2018. Hrsg.: T. P. Kersten, 34–48, Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation, München.
Keller, S.; Riese, F. M.; Stötzer, J.; Maier, P. M.; Hinz, S. (2018). Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences - Symposium “Innovative Sensing – From Sensors to Methods and Applications”, Karlsruhe, Germany, 10–12 October 2018. Volume: IV-1, 101–108, ISPRS. doi:10.5194/isprs-annals-IV-1-101-2018
Riese, F. M.; Keller, S. (2018). Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22nd - 27th July, 2018, 6151–6154, IEEE, Piscataway, NJ. doi:10.1109/IGARSS.2018.8517812
Riese, F. M.; Keller, S. (2018). Fusion of hyperspectral and ground penetrating radar data to estimate soil moisture. 9th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (Whispers 2018), Amsterdam, NL, September 23-26, 2018, IEEE. doi:10.1109/WHISPERS.2018.8747076
Projects
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