Kerstin Rau
Address:
Eberhard Karls University Tübingen
Soil Science and Geomorphology
Rümelinstraße 19-23
D-72070 Tübingen
Office: Westbau W304
Consulting hours:
by arrangement
Function: Doctoral student
CV:
18th April 1995 in Wangen im Allgäu, Germany
Project:
Cluster of Excellence Machine Learning EXC 2064/1: Interpretable spatial machine learning for environmental modelling
Education:
Since 04/2020 | PhD student at the Eberhard Karls Universität of Tübingen, Germany |
10/2019 | First Staatsexamen for the teaching profession at grammar schools Thesis in Mathematics: ‘Assoziierte Primideale‘ (apl. Prof. Dr. Thomas Markwig, Tübingen) |
10/2013 - 10/2019 | Studies in Geography and Mathematics at University of Tübingen, Germany |
Field work:
Nahuelbuta and La Campana, Chile (biocrust sampling, soil erosion survey) |
Mesa Redonda, Villaverde del Río, Spain (soil sampling and mapping) |
Memberships:
- DBG: Deutsche Bodenkundliche Gesellschaft (Link) [German Soil Science Society]
- EGU: European Geosciences Union - Soil System Sciences (Link)
Public outreach:
since April 2024: Member of the Social Media Team of the Strength and Fitness Center of the University of Tübingen (https://uni-tuebingen.de/einrichtungen/zentrale-einrichtungen/hochschulsport/kraft-und-fitnesshalle/) |
since April 2023: Member of KI macht Schule (https://ki-macht-schule.de/) at the local group Tübingen |
April and July 2023: Workshops with Deutsche Schule Rom und Freiherr-vom-Stein Schule Eppstein |
February to October 2023: Demo of my research at the Stadtmuseum Tübingen in the exhibtion "Cyber and the City: Künstliche Intelligenz bewegt Tübingen" |
November 2022: Winner of the outreach projekt "I'm a Scientist, get me out of here: Runde KI" |
July 2022: Demo of my research at Science & Innovation Days Tübingen |
September 2021: Co-organizor for the first ELLIS Doctoral Symposium 2021 in Tübingen |
Teaching:
SS24 | Lecture “Soil Science” (University of Applied Forest Sciences Rottenburg) |
SS24 | Exkursion im Rahmen von GEO21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
SS23 | Exkursion im Rahmen von GEO21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
SS22 | Exkursion im Rahmen von GEO21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
SS21 | Exkursion im Rahmen von GEO21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
SS19 | Tutorin für GEO 21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
WS18/19 | Tutorin für GEO 14 Kartographie und Statistik (Dr. Hans-Joachim Rosner) |
SS18 | Tutorin für GEO 21 Bodenkunde und Geomorphologie (Prof. Dr. Thomas Scholten) |
WS17/18 | Tutorin für GEO 14 Kartographie und Statistik (Dr. Hans-Joachim Rosner ) |
Publications
2024
Rau, K., Eggensperger, K., Schneider, F., Hennig, P. and Scholten, T. (2024). How can we quantify, explain, and apply the uncertainty of complex soil maps predicted with neural networks? Science of The Total Environment, 944, 173720. p. doi: 10.1016/j.scitotenv.2024.173720
Conference Contributions:
2024
Rau, K.., Eggensperger, K., Schneider, F., Hennig, P., & Scholten, T.: How can we quantify, explain and apply the uncertainty of complex soil maps predicted with neural networks? EGU General Assembly 2024, Vienna, Austria. [talk]
Rau, K., Eggensperger, K., Schneider, F., Hennig, P., & Scholten, T.: How can we quantify, explain and apply the uncertainty of complex soil maps predicted with neural networks? Centennial of the IUSS 2024, Florence, Italy. [talk]
2023
Rau, K., Eggensperger, K., Schneider, F., Hennig, P., & Scholten, T.: How can we quantify, explain and apply the uncertainty of complex soil maps predicted with neural networks? AHM of the German AI Competence Centers, Berlin, Germany. [poster]
Rau, K., Eggensperger, K., Schneider, F., Hennig, P., & Scholten, T.: How can we quantify, explain and apply the uncertainty of complex soil maps predicted with neural networks? Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2023, Halle, Germany. [talk]
2022
Rau, K., Gläßle, T., Hennig, P., & Scholten, T.: Spatial prediction of soil type maps with Neural Networks including quantification of model uncertainty. 22nd World Congress of Soil Science 2022, Glasgow, United Kingdom. [poster]
Rau, K., Gläßle, T., Hennig, P., & Scholten, T.: Spatial prediction of soil type maps with Neural Networks including quantification of model uncertainty. ELLIS Doctoral Symposium 2022, Alicante, Spain. [poster]
Rau, K., Gläßle, T., Hennig, P., & Scholten, T.: Spatial prediction of soil type maps with Neural Networks including quantification of model uncertainty. Jahrestagung der Deutschen Bodenkundlichen Gesellschaft 2022, Trier, Germany. [talk]
Rau, K., Gläßle, T., Hennig, P., & Scholten, T.: Spatial prediction of soil type maps with Neural Networks including quantification of model uncertainty. EGU General Assembly 2022, Vienna, Austria. [talk]
Gläßle, T., Rau, K., Scholten, T., & Hennig, P.: Hierarchical Soil Classification using Gaussian Processes. EGU General Assembly 2022, Vienna, Austria. [talk]
2021
Rau, K., Gläßle, T., Rentschler, T., Hennig, P., & Scholten, T.: Spatial prediction of soil thickness with Gaussian Process Regression using pedological knowledge described by partial differential equations. EGU General Assembly 2021, Vienna, Austria. [vPICO]
Gläßle, T., Rau, K., Schmidt, K., Scholten, T., & Hennig, P.: Topographic Kernels for Gaussian Process Regression in Digital Soil Mapping. EGU General Assembly 2021, Vienna, Austria. [vPICO]