Kerstin Rau

Address:

Eberhard Karls University Tübingen
Soil Science and Geomorphology
Rümelinstraße 19-23
D-72070 Tübingen

Office: Westbau W304

Contact:

+49(0)7071-29-78-943

kerstin.rauspam prevention@uni-tuebingen.de

Consulting hours:

by arrangement

Function: Doctoral student

Web of Science: Visit Web of Science    ORCID:     Google Scholar: 

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
since August 2024: Team leader of 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]