I'm a Senior Scientific Python & ML Engineer with 10+ years of experience in mathematical modeling, numerical simulation, data analysis, and research software engineering.
I build reliable, maintainable Python tools for scientific and technical problems, from simulation workflows and data pipelines to applied machine learning systems.
- Scientific Python and research software
- Mathematical modeling and numerical simulation
- Data analysis, visualization, and validation
- Geospatial and spatial-database tooling
- Workflow automation and reproducible pipelines
- Applied machine learning
- Robust, maintainable code for scientific users
I contribute to tools and workflows used in geospatial applications, computational neuroscience, scientific data processing, and reproducible research software.
- GeoAlchemy2: geospatial extension to SQLAlchemy for working with spatial databases.
- GeoAnnotator: full-stack web application for geospatial annotation, built with Django, PostGIS, React, TypeScript, Docker, and monitoring tooling.
- axon-synthesis: scientific Python package for synthesizing artificial axons in computational neuroscience workflows.
- morphology-workflows: scientific Python workflows for processing neuronal morphologies, including fetching, curation, annotation, repair, transformation, and reproducible reporting.
- data-validation-framework: Luigi-based framework for building data validation workflows.
- luigi-tools: utilities extending Luigi for complex workflow and pipeline development.
- dir-content-diff: Python tool for comparing generated directory contents with reference outputs.
- Open-source scientific software
- Machine learning for scientific modeling and simulation
- Reproducible research workflows
- Geospatial data tools
- Research software quality
- Languages: Python, C++, Rust, SQL
- Scientific Python: NumPy, pandas, SciPy, Dask, PyTorch
- Visualization: Matplotlib, Seaborn, Plotly
- Databases and geospatial: PostgreSQL, PostGIS, SQLAlchemy, GeoAlchemy2
- Workflow and data tools: Luigi, data validation, reproducible pipelines
- Python tooling: uv, pip, Ruff, pytest
- Web and infrastructure: Django, React, TypeScript, Docker, Git