Literature review
Belbèze, S., Rohmer, J., Négrel, P., Guyonnet, D. (2023). Defining urban soil geochemical backgrounds: A review for application to the French context; Journal of Geochemical Exploration. 254, 107298.
CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
group-SHAP uncertainty
Rohmer, J., Belbeze, S., and Guyonnet, D.: Insights into the prediction uncertainty of machine-learning-based digital soil mapping through a local attribution approach, SOIL, 10, 679–697, https://doi.org/10.5194/soil-10-679-2024, 2024.
Geospatial Uncertainties with Intervals
Labourg, P., Destercke, S., Guillaume, R., Rohmer, J., Quost, B., Belbèze, S. (2024). Geospatial Uncertainties: A Focus on Intervals and Spatial Models Based on Inverse Distance Weighting. In: Lesot, MJ., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2024. Lecture Notes in Networks and Systems, vol 1174. Springer, Cham. https://doi.org/10.1007/978-3-031-74003-9_30
Sensitivity Analysis
Rohmer, J. (2025). Importance Ranking of Modelling Choices in Quantile Regression Forest-Based Spatial Predictions When Data are Sparse, Imprecise and Clustered; Ecological Informatics. Submitted
Talks
Introduction Talk at ANR
Talk at Virtual meeting, ANR
Explicability in Machine learning for Geoscience processes
Talk at Virtual meeting, GDR MADICS
Spatial prediction with spatially clustered data by combining residual kriging and instance-based transfer learning
Presentation at journees de la Geostatistique, Fontainebleau (France)
IPMU 2024 conference
Talk at Lisboa (Portugal), Lisboa (Portugal)
Teaching
Service and leadership
- Currently signed in to 43 different slack teams