Function and Responsibilities:

Applied mathematician performing gravity field retrieval simulations

Research Interests:

Career:

Projects:

March 2019 – 2021

• Development of SNAP pipeline in python for the calculation of land subsidence from SAR Sentinel1 images.

• Modelled suspended particle matter in the Wadden sea using stacked ensemble machine learning methods.

• Developed Flask based API for doing pre-processing for chemical and biological input components to the DFlowFM model.

• Developed and deployed docker containers for Jupyter notebooks on Azure. These notebooks were for online courses at Deltares.

• Developed a gradient boosting based machine learning model to predict overtopping at coastal structures.

December 2015-February 2019

• Developed a river routing model to simulate the movement of surface runoff to oceans on a global scale. 

• Constructed an interface that converts weather data from three different sources into a standard format and combines these into a single database. 

• Constructed models to predict overtopping at coastal structures with OpenFOAM (IHFoam).

• Trained feedforward and recurrent neural networks on river discharge data.