Applied Mathematician | Computational Systems Biology | Scientific Software Engineer
I build computational tools for mechanistic modeling, data analysis, and high-performance simulation in life sciences.
Core areas: • Systems biology • HPC parameter estimation • Scientific software • Data analysis pipelines
🔬 Research focus
- Mechanistic modeling (ODE/PDE)
- Systems biology & metabolic networks
- HPC parameter estimation
- AI-assisted modeling
💻 Technical stack
Python | R | Julia | C++ | HPC | Docker | Kubernetes | SLURM
📦 Featured projects
- Shiny-Calorie (indirect calorimetry analysis)
- VRL-SWC-Density-Vis (neuron morphology analysis)
- NeuroBox3D plugins
📄 Publications ORCID
📬 Contact
Contact information can be found on the left most panel - feel free to browse my recent and public projects.
For secure e-mailing find my GPG fingerprint as: F598 BCFF 445C C90F 3312 3C71 7D30 C7E5 7559 76A6.
I am an applied mathematician who has completed postdoctoral research positions as detailed below.
I am currently planning to transition from academia to an R&D role in industry by the end of 2026. My work focuses on applying both novel and established mathematical methods to problems in systems biology, with the goal of supporting pre-clinical and translational research in the life sciences.
Selected examples of my work are presented below. If my background and skills align with your organization's interests, I would be very happy to connect. Please feel free to reach out using the contact information provided.
Up to mid of 2026, I am/was a postdoctoral fellow in the lab of Jan Hasenauer where my research revolves around the interfaces of life sciences, mathematics and computer science. We developed mechanistic models (ODE/PDEs) and applied methods of parameter estimation in Julia/Python to calibrate models and to shed light on the interplay / ramifications of dynamical biological processes in cells in the special research fields BATenergy and Metaflammation. Therefore we leveraged AI-tools, artificial neural networks/deep learning approaches and recent advances in bioinformatics on high-performance computing infrastructure. We developed pipelines for statistical data analysis and visualization (R/Python, Javascript/Typescript) of large-scale data sets, knowledge representation and reasoning on metadata using semantic web technologies (graph databases, SPARQL, ontologies in OWL format) focusing on reusability, repeatability and reproducibility.
I've actively maintained / contributed to the following repositories:
- https://github.com/ICB-DCM/pyABC - a framework for distributed, likelihood-free inference
- https://github.com/stephanmg/calorimetry - a Shiny/R application for analysis of indirect calorimetry datasets
- https://github.com/ICB-DCM/pyPESTO - a python Parameter EStimation TOolbox
- https://github.com/stephanmg/Shiny-PWAS - a Shiny/Python application to access the ExPheWas database
Up to 2020 I have been working in the field of computational neuroscience under supervision of the Queisser lab. I developed novel numerical methods and grid generation tools for modelling and simulation of spatially-resolved intracellular ion dynamics in neurons by PDEs/ODEs on HPC/HTC infrastructure. We made use of GPU programming on NVIDIA GPUs through CUDA/cg shader programming for interactively visualizing and numerical analysis of scientific data sets in the virtual reality framework Unity VR (C#). Major programming experience stems from C++/C and Lua, Java and Python. I developed prior to that also numerical models for multi-scale and hybrid-dimensional phenomena in molecular dynamics/computational neuroscience and mesh generation methods for the study of intracellular Calcium waves, neuronal plasticity and memory formation.
I have been a contributor to the following repositories:
- https://github.com/c2m2/Neuro-VISOR/ - Virtual Interactive Simulation Of Reality for simulation of neuronal dynamics
- https://github.com/ug4 - UG4 simulation framework. Solving differential equations on unstructured finite element grids.
- https://github.com/NeuroBox3D - A visual toolbox for simulation of neuronal activity in hybrid 1D/3D settings
- https://github.com/stephanmg/VRL-SWC-Density-Vis - A Java application for density analysis of stacks of neuronal morphologies (NeuroMorpho.org)
You can find my works on ResearchGate.