Oliver E.

Math modeling, PDEs, numerical methods, Python, Rust, Fortran, C++, Julia, Kubernetes, machine learning, parallel programming, high performance computing, data analysis, error analysis. In my master's thesis, I developed a math model to describe the light field in a seaweed farm, wrote an object-oriented Fortran 90 code, parallelized with OpenMP, to solve the resulting PDE using a finite difference algorithm and less computationally expensive asymptotic approximation for multiple discrete scattering events. I performed a detailed error analysis of the two algorithms to determine necessary grid size and applicable conditions for the discrete scattering approximation for a desired level of accuracy. I wrote a Python wrapper using F2PY for the F90 code, and interactive Jupyter widgets to allow highly parallelized simulations to be launched en masse over large parameter spaces from Jupyter notebooks to a remote kubernetes cluster. Other research interests: - Interactive high performance computing - Group decision making - Machine learning - Virtual reality - Interactive data visualization Miscellaneous skills: - Linux - LaTeX - Web development - Image processing / graphic design - Audio/video editing/recording