Robin Thibaut
Computational Geoscientist @ Zanskar Geothermal & Minerals

Computational geoscientist specializing in Bayesian uncertainty quantification for geothermal exploration. Develop Python-first workflows that integrate thermal simulation, geophysics, and well data to optimize drilling targets and quantify resource uncertainty.
Research Focus: Experimental design · Physics-informed ML · Subsurface characterization
Core Expertise
Programming & ML:
- Python (NumPy, Pandas, scikit-learn, PyTorch, TensorFlow)
- Uncertainty Quantification (Bayesian, BEL)
- Experimental Design & Physics-informed ML
- Time-series & Spatial Modeling
Geoscience Modeling:
- Finite-element thermal simulation
- MODFLOW, MT3DMS, MODPATH, ModelMuse
- Geophysical Data Integration (CRTOMO, RES2DINV, ERT/IP)
- SGeMs, Hydrologic & Groundwater Modeling
Data & Engineering:
- SQL, Snowflake, Git, ETL/Data Engineering
- Cloud (Google Cloud Platform), CI/CD
- Scientific Visualization
- Linux/macOS/Windows
Highlighted Publications
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Comparing Well and Geophysical Data for Temperature Monitoring First Author | Water Resources Research (2022) | DOI: 10.1029/2022WR033045
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A Framework for Bayesian Experimental Design in Environmental Geosciences First Author | Journal of Hydrology (2021) | DOI: 10.1016/j.jhydrol.2021.126903 | Repo: skbel
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Minimum Gradient Support Inversion for Resistivity/IP Data First Author | Journal of Applied Geophysics (2021) | DOI: 10.1016/j.jappgeo.2021.104286 | Repo: MGS-public
Open Source Software & Resources
Software Packages:
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SKBEL - Bayesian Evidential Learning framework DOI: 10.5281/zenodo.6205242 - MGS-public - Minimum Gradient Support inversion for resistivity/IP data
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pysgems - Use SGeMS (Stanford Geostatistical Modeling Software) within Python DOI: 10.5281/zenodo.4773587 - Python Scientific Project Template - Standardized structure for scientific Python projects
Datasets:
- Zanskar’s GeoGym - Benchmark dataset for evaluating geothermal exploration strategies
- 4D ERT Monitoring Dataset - Temperature monitoring with geophysical data
- Wellhead Protection Area Prediction Dataset - Groundwater modeling and protection
Featured Blog Posts
- The Importance of Python for Geoscientists
- Why the Rainbow Color Map is Problematic
- A Gentle Introduction to Python with PyCharm
GitHub Stats
news
Oct 02, 2024 | SLC Bound! 🏔️ |
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Aug 02, 2023 | Berkeley Bound! 🌁 |
Mar 28, 2023 | PhD defended! |
Mar 09, 2023 | Public PhD defense. "Machine Learning for Bayesian Experimental Design in the Subsurface" |