About me.

My passion is solving complex real world problems from the realm of transport equations on modern HPC architectures.
Most recently, my interests focus on useful applications of machine learning and GPGPU acceleration techniques.
Being a quick learner and reliable team player, I have been working on a wide range of successful projects with fellow Ph.D. students as well as industry partners.
As I am now close to finishing my Ph.D. at Karlsruhe Institute of Technology in late Oktober, I am already looking forward to new and exiting challenges.

Projects.

ZEBRA

EFRE.NRW Project

As a winner of the market competition EnergieUmweltwirtschaft.NRW, the federal state NRW funded innovative developments in the field of environmental technologies with the help of European Union funds. In cooperation with AiNT GmbH an innovative measurement system was developed for non-destructive environmental and hazardous substance analysis. This measurement system is based on the prompt and delayed gamma neutron activation analysis (P&DGNAA). The project included the development of new analytical methods for determining the mass fractions of materials inside an unknown sample.

Finite element method, Particle transport, Inverse problems, Uncertainty quantification, Sparse reconstruction

Python, C++, MPI, OpenMP, Docker, gRPC

UQCreator

HPC Uncertainty Quantification framework

The uncertainty quantification framework UQCreator provides various uncertainty propagation tools for hyperbolic conservation laws. Its main idea is to use kinetic numerical fluxes and source terms, which evaluate a given deterministic problem at different sample points. This hybridization of intrusive and non-intrusive methods significantly reduces numerical costs, yields an efficient parallelization with OpenMP and MPI while allowing an easy extension to various problems into the framework.

Uncertainty quantification, Finite volume method

C++, MPI, OpenMP

KiT-RT

HPC Radiation Therapy framework

The KiT-RT (Kinetic Transport Solver for Radiation Therapy) framework is a high-performance open source platform for radiation transport. Its main focus is on radiotherapy planning in cancer treatment. Furthermore, it also provides tools to investigate various research questions in the field of radiative transfer. This goal is supported by an easily extendable code structure that allows for straightforward implementation of additional methods and techniques.

Particle transport, Finite volume method

C++, Python, MPI, OpenMP

Renewable Energy

Sensitivity Analysis for Offshore Wind Farms

As uncertainties in modeling/input parameters like wind direction, turbine energy generation characteristics and economic factors are crucial in the prediction of the annual power production of an offshore wind farm and generally very difficult to assess, we developed a powerful tool to quantify the effects of these uncertainties for arbitrary wind farms. The tools makes use of advanced techniques for high dimensional numerical integration and therefore is capable of computing comprehensive sensitivity information with low computational effort.

Renewable energy, Uncertainty quantification

C++, OpenMP

Jannick Wolters

Applied

Mathematician

About me.

Experience.

Education.

ongoing

Software Development Engineer

ongoing

Ph.D. in Mathematics

03/2017 - 05/2021

Research Scientist

04/2015 - 03/2017

Master of Computational Engineering Science

03/2017 - 05/2021

Student research / teaching assistant

10/2013 - 03/2014

Research Internship

10/2010 - 03/2015

Bachelor of Computational Engineering Science

Skills.

Mathematics

Computer Science

Software Packages

Topics

Numerical Methods

Equations

HPC

Data Science

Software development

Languages

Fluid Dynamics

Particle transport

IDE's