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Max Ramgraber is an Assistant Professor at Delft University of Technology, Netherlands, specializing in uncertainty estimation and data assimilation within hydrogeology. His research focuses on the development of statistical methods to quantify uncertainties in environmental systems, particularly in subsurface environments where data is often sparse and incomplete. He employs advanced data assimilation algorithms to improve model parameters over time, enhancing the self-improving nature of simulations used in applications such as automated control systems and GPS tracking. With a Ph.D. from the Swiss Federal Institute of Aquatic Science and Technology (Eawag) and experience as a postdoctoral researcher at the Massachusetts Institute of Technology, Ramgraber combines rigorous numerical modeling techniques with uncertainty quantification to address challenges in groundwater studies. His work aims to create physically meaningful connections in the fragmented information of subsurface properties and to contribute to the reliability of groundwater resources, which are critical freshwater reservoirs globally.
Delft University of Technology • Delft, Netherlands
Teaching and researching in the field of environmental engineering, focusing on uncertainty estimation and data assimilation.
Massachusetts Institute of Technology • Cambridge, USA
Conducted research in data assimilation and statistical methods in environmental systems.
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