Job offer : PhD Thesis (2023-2026)
Uncertainties and imprecision in Spatial Interpolations for Urban Risk Mapping
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portfolio
Benchmark Sparse Imprecise Clustered data
Overview of representative challenges for spatial interpolation
Portfolio item number 2
Short description of portfolio item number 2 
publications
Literature review
Published in Journal of Geochemical Exploration, 2023
A literature review of methods used to establish urban soil geochemical background
Recommended citation: 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. https://www.sciencedirect.com/science/article/abs/pii/S0375674223001450
group-SHAP uncertainty
Published in SOIL, 2024
Insights into the prediction uncertainty of machine-learning-based digital soil mapping through a local attribution approach
Recommended citation: 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. https://soil.copernicus.org/articles/10/679/2024/
Geospatial Uncertainties with Intervals
Published in Lecture Notes in Networks and Systems, 2024
Recommended citation: 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 https://doi.org/10.1007/978-3-031-74003-9_30
Sensitivity Analysis
Published in Ecological Informatics, 2025
Importance Ranking of Modelling Choices in Quantile Regression Forest-Based Spatial Predictions When Data are Sparse, Imprecise and Clustered
Recommended citation: 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 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5095837
talks
Introduction Talk at ANR
Published:
Introduction to ANR-HOUSES presented at the ANR H-16 “Interface between Mathematics, Environmental and Earth sciences” axis virtual meeting. Download presentation here
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Explicability in Machine learning for Geoscience processes
Published:
Introduction to problems related to explicability of Machine learning models for Geoscience processes presented at the GDR MADICS. Download presentation here
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Spatial prediction with spatially clustered data by combining residual kriging and instance-based transfer learning
Published:
Presentation on the benefits of transfer learning to overcome the limits of clustered data presented at the journees de la Geostatistique. See presentation here. Download abstract here.
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IPMU 2024 conference
Published:
Talk by Priscillia Labourg on “Geospatial uncertainties: a focus on intervals and spatial models based on inverse distance weighting” presented at the IPMU conference “20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems”
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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