I am a computational materials scientist working at the interface of materials science, scientific workflows, high-performance computing, machine learning, and agentic AI.
I lead the Materials Informatics Group at the Max Planck Institute for Sustainable Materials. My research focuses on turning expert computational procedures into reproducible, scalable, interoperable, and increasingly autonomous scientific workflows.
Materials science → scientific workflows → HPC → machine learning → agentic science
Current topics include automated atomistic simulation and thermodynamics, uncertainty quantification, machine-learned interatomic potentials, workflow interoperability, HPC execution, and LLM-based scientific agents.
I contribute to and lead open-source projects where testing, reproducibility, and sustainable software engineering are part of the research output.
| Project | Scope | Publication | Coverage | GitHub Stars |
|---|---|---|---|---|
| pyiron/pysqa (2026) | HPC queuing system adapter | JOSS | ||
| pyiron/executorlib (2025) | Scale Python functions to HPC | JOSS | ||
| pythonworkflow/python-workflow-definition (2025) | Workflow interoperability | Digital Discovery | ||
| jan-janssen/LangSim (2025) | LLM agents for atomistic simulation | MLST | — | |
| pyiron/pyiron (2019) | Computational materials science environment | CMS | — |
I also build small automation tools for repetitive digital tasks.
| Project | Scope | Coverage | GitHub Stars |
|---|---|---|---|
| gmailsorter | Automated email sorting | ||
| pyauthenticator | Programmatic 2FA workflows | ||
| conda-forge-contribution | Contributor Statistics |
More about the group, tutorials, and teaching material: github.com/janssenlab