I'm a PhD student and Research Software Engineer at SimTech in Stuttgart, working on scientific modelling, research data management, and software infrastructure for discovery.
Most days, you'll find me tinkering with tools for scientific computing and complex data workflows, using Python and Rust. My passion lies in making scientific data more accessible and reproducible, from developing data standards to creating workflow automation and frameworks for biochemical modeling systems.
Focus areas: Scientific computing, high-performance computing (HPC), research data infrastructure, and machine learning for real-world biochemical challenges.
EnzymeML — Developed a complete ecosystem of libraries for the EnzymeML data standard, enabling FAIR and reproducible enzyme kinetics data exchange. Built APIs across Python, Rust, Julia, TypeScript, and Go.
EnzymeML Suite — Cross-platform desktop application built with Tauri, React, and TypeScript for managing enzyme kinetics data with integrated Jupyter workflows and AI-powered data extraction.
Catalax — JAX-based framework for biochemical modeling with automatic rate law generation, neural ODEs, and Bayesian parameter inference. Combines symbolic computation with high-performance numerical methods.
Harvard Dataverse Libraries — Maintain and develop the official client libraries for Harvard Dataverse: pyDataverse, easyDataverse, and rust-dataverse. These libraries provide programmatic access to one of the largest research data repositories.