Dr.sc.nat M. (Max) Ramgraber
Dr.sc.nat M. (Max) Ramgraber
Profiel
More information on my personal website.
Research Interests
Uncertainty Estimation and Parameter Inference
Most of my research revolves around uncertainty estimation. Information about environmental systems is often scarce, and the consequence is uncertainty. Statistical methods allows us to quantify this uncertainty where it cannot be otherwise resolved. This is critical in the study of the subsurface, one of the most information-limited environmental systems. I am particularly interested in statistical methods which allow us to capture advanced aspects of uncertainty such as Pareto frontiers, multi-modality, and other non-Gaussian features.
Data assimilation is a specialized form of uncertainty estimation. It plays an important role in systems where we have an interest in sequential or real-time updates to our simulations. Examples include weather forecasts, automated pump control, petroleum engineering, or GPS tracking. Advanced data assimilation algorithms can even infer and improve a model's parameters with time, yielding self-improving simulations. Much of my work focusses on such algorithms.
The context in which I explore these subjects is often hydrogeology. Groundwater is the most important freshwater reservoir in many parts of the world. Unfortunately, the subsurface is mostly unobservable, which makes its study challenging. With predominantly point-wise data, numerical models are an important tool to create physically meaningful connections between these fragmented pieces of information. When combined with uncertainty estimation, we can rigorously study the plausibility and consequences of different hypotheses about the subsurface's properties even with incomplete data.
Brief CV
2021 - 2023 Postdoctoral Researcher at Massachusetts Institute of Technology, Cambridge, USA
2016 - 2020 Doctorate at Swiss Federal Institute of Aquatic Science and Technology (Eawag), Zürich, Switzerland, and the University of Neuchâtel, Switzerland
2014 - 2016 Applied & Environmental Geoscience M.Sc. at Eberhard-Karls-Universität Tübingen, Germany
2011 - 2014 Geoscience B.Sc. at Christian-Albrechts-Universität zu Kiel, Germany
Expertise
Publicaties
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2023-11
Ensemble transport smoothing. Part I: Unified framework
Maximilian Ramgraber / Ricardo Baptista / Dennis McLaughlin / Youssef Marzouk
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2023-11
Ensemble transport smoothing. Part II: Nonlinear updates
Maximilian Ramgraber / Ricardo Baptista / Dennis McLaughlin / Youssef Marzouk
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2021-6
Hydrogeological Uncertainty Estimation With the Analytic Element Method
Maximilian Ramgraber / Mario Schirmer
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2021-4
Non‐Gaussian Parameter Inference for Hydrogeological Models Using Stein Variational Gradient Descent
Maximilian Ramgraber / Robin Weatherl / Frank Blumensaat / Mario Schirmer
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2020-6
Quasi‐Online Groundwater Model Optimization Under Constraints of Geological Consistency Based on Iterative Importance Sampling
Maximilian Ramgraber / Matteo Camporese / Philippe Renard / Paolo Salandin / Mario Schirmer
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Onderwijs 2024
- Modelling, Uncertainty and…
- Data Assimilation for the…
- Advanced Reservoir…
- Probabilistic Modelling of…
Onderwijs 2023
Media
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2024-07-19
Dertien veelbelovende jonge Delftse onderzoekers ontvangen Veni-beurs
Verscheen in: TU Delft
Prijzen
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2021-11-16
Prix Léon du Pasquier et Louis Perrier
An prize awarded annually for a single excellent dissertation with the University of Neuchâtel's Faculty of Science:
En mémoire de Léon Du Pasquier (1864-1897) et de Louis Perrier, un prix, intitulé prix « Léon Du Pasquier et Louis Perrier », est institué et est décerné annuellement (ou tous les deux ans) par la Faculté des sciences pour récompenser une excellente thèse de doctorat dans l’un des domaines scientifiques de la Faculté des Sciences.
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2018
Outstanding Student Poster and PICO (OSPP) Award
EGU General Assembly 2018
Nevenwerkzaamheden
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2023-08-01 - 2025-07-31