Projects

KI‑Morph is platform for the image analysis of large 3D imaging data (e.g., micro‑CT, MRI, light‑sheet, confocal). It automates and accelerates key annotation steps with cutting‑edge AI and infrastructure to reduce manual effort and improve accuracy. I serve as research program manager, steering the roadmap, designing architecture, developing AI workflows, and advancing visualization tools.

YoKI is Heidelberg University’s on‑premises, LLM platform running a set of curated models exclusively on university servers for privacy and compliance. Accessible from campus or via VPN, prompts never leave the university and are not retained for training. As part of the core team, I drive direction and architecture, ensure compliance, and conduct user outreach.

The mathematical oncology community website is a community hub advancing mathematical and computational approaches to understand and predict cancer. It brings together blog posts, a weekly newsletter, curated open‑source datasets, and listings for seminars, conferences, jobs, and resources. As editor, I integrate new blog posts and maintain the website from a technical perspective.

PLSD.eu is the front‑end to the Prospective Lynch Syndromes Database, one of the largest databases for hereditary cancer research. As technical lead, I oversee software architecture, development and UI/UX.

We applied mathematical modeling to oncology to interpret complex genomic and clinical data and derive actionable medical insights. Using Lynch syndrome as a model system, we studied tumor evolution, elevate tumor immunology to a genome‑wide level, and predict the efficacy of diagnostics, prevention, and treatment. My research work focused on the analysis of large image data to determine tumor heterogeneity as well as the analysis of genetic data for the prediction of a certain genetic predisposition.

In this research project we developed novel methods for low-level image analysis on statistical manifolds. I have contributed research and code to the development of the numerical integration schemes and approximation algorithms for efficient computation.

Beyond the projects described above, I have provided consulting across software engineering, data analysis, and applied machine learning for organizations ranging from startups to multinational corporations and academic groups. I have supported researchers in the fields of medicine, biology, astrophysics, cybersecurity, psychiatry, and more with software engineering, data analysis and artificial intelligence.