I develop computational methods and AI-powered remote sensing tools to study complex Earth systems — from subsurface fluid dynamics and carbon storage to satellite-based mapping of rivers, coastlines, forests, and natural hydrogen reservoirs.
I grew up in the Netherlands and received my undergraduate and MSc degrees in Physics, Astronomy, and Geophysics at Utrecht University. I was fortunate to study under Nobel Laureate Gerard 't Hooft for my Physics MSc and under Jan Kuijpers for Astronomy. I then completed my PhD at Radboud University Nijmegen (2001–2006) in general-relativistic plasma dynamics, followed by postdoctoral work at the University of Rochester (2006–2008) on a NASA grant studying Poynting-flux-dominated astrophysical outflows.
In late 2008 I made a deliberate pivot to Earth sciences, joining the Reservoir Engineering Research Institute (RERI) in Palo Alto as a postdoctoral researcher with Abbas Firoozabadi. There I spent five years developing higher-order finite element methods for compositional multiphase flow in fractured porous media — work that laid the foundation for my research program at OSU. I joined the School of Earth Sciences as an Assistant Professor in 2013, was promoted to Associate Professor in 2019, and to Full Professor in 2024.
During my 2020–2021 sabbatical I pivoted again, this time toward deep learning applied to multi-modal satellite imagery. That direction has since grown into my primary research focus, institutionalized through the BuckAI Observatory, which I founded in August 2025 with $1M in OSU seed funding. My group now works on AI-driven problems ranging from shallow-water bathymetry and river dynamics to global mapping of natural hydrogen reservoirs and deforestation monitoring in Sub-Saharan Africa.
Higher-order finite element methods for multiphase compositional flow, discrete fracture networks, CO₂ sequestration, flow instabilities, and natural hydrogen reservoirs. Over 15 years of method development, 4 patent families, and collaboration with DOE and industry.
Explore this direction →Deep learning applied to commercial and freely available satellite imagery for river classification, super-resolution water mapping, coastal bathymetry via physics-informed AI, global hydrogen prospecting, and deforestation tracking in Africa.
Explore this direction →AGU TV Thought Leadership Film
Research Overview