I’m a researcher at the Max Planck Institute of Molecular Plant Physiology with an MSc in Plant Sciences from LMU Munich. I work at the intersection of biology, data analysis, and scientific software development, building tools that make research data easier to explore and understand.
An R Shiny application for proteomics data analysis and visualization. ProteATO brings interactive analysis into an accessible interface for exploring biological datasets.
I contribute to openJII, an open source platform for photosynthesis data. This work connects my plant science background with collaborative scientific software development.
An interactive Principal Component Analysis visualization built with React and Vite, designed to make PCA easier to explore and understand.
- Scientific computing: R, Python, NumPy, SciPy, Pandas
- Applications and visualization: R Shiny, Plotly, React, TypeScript, Vite
- Machine learning: scikit-learn, TensorFlow
- Data and development tools: PostgreSQL, MongoDB, Git, GitLab, Jupyter, VS Code
- Research computing: Linux, Bash, SSH
- Bioinformatics and proteomics data analysis
- Scientific software and reproducible research workflows
- Interactive data visualization
- Machine learning for biological research
- Open source collaboration
