Blending Geosciences with Artificial Intelligence
John Lab — OSU CEOAS
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Advancing geosciences through multidisciplinary research since 2008. We focus on novel deep learning algorithms for the energy transition and climate adaptation — both in terms of fundamental AI development and applied AI.
2008 – 2015 · Imperial College London
Early Days: Carbonate Focus
Dr. John joins the Department of Earth Science and Engineering at Imperial College London as an assistant professor and founds the lab — initially called the "Carbonate Research Group". It is focused on carbonate sedimentology, stratigraphy, and diagenesis, blending computational Earth sciences (forward modelling, geostatistics) with isotope geochemistry (clumped isotopes) and fieldwork.
2015 – 2024 · Imperial College London
Pivoting to AI
Dr. John progressively shifts the lab toward data science, machine learning, and deep-learning computer vision applied to geosciences. In 2022, it is rebranded simply "John Lab" to reflect this broader remit, and becomes heavily involved in Imperial's AI initiatives, notably I-X and the Data Science Institute.
2024 – 2026 · Queen Mary University of London
Digital Environment Research Institute
Dr. John and his lab join the Digital Environment Research Institute at Queen Mary University of London, a multidisciplinary AI institute. This deepens the lab's commitment to fundamental AI and AI-driven solutions for environmental and climate challenges.
2026 – Present · Oregon State University
AI Powerhouse in the Pacific Northwest
The lab is moving to Oregon State University's College of Earth, Ocean and Atmospheric Sciences, a world leader in geoscience. Thanks to a generous gift from OSU alumnus Jensen Huang (founder and CEO of NVIDIA), OSU is building one of academia's most powerful AI supercomputers — the ideal home for AI-driven Earth science at scale.
Continuing academic affiliations
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2024 – 2028
Imperial College London
Visiting Professor
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2026 – 2031
Digital Environment Research Institute, Queen Mary University of London
Visiting Professor
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2026
Hyperlocal Weather Forecasting by Machine Learning: Findings, Results, and Conclusions of the IEEE Region 8 Competition
AlSalmi et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, V.19
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2026
Geochronology and mantle origin of CO2-rich fluid flow in a Cretaceous carbonate reservoir, offshore Angola
Rochelle-Bates et al. · Marine Geoscience and Energy Resources, V. 194
- 2026
Editorial