I'm a passionate Geospatial Data Scientist with a diverse interdisciplinary background spanning Chemistry (Diplom-Chemiker), Electrochemistry, Computer Science, and Data Science. Currently pursuing my M.Sc. in Data Science while working on cutting-edge renewable energy analytics.
🔬 Master's Thesis: "Validation of Photovoltaic Data in the German Core Energy Market Register via Aerial Image Segmentation"
🛠️ Combining Deep Learning, Geospatial Analysis, and Renewable Energy research
📊 5+ years as Data Scientist at Delphi IMM GmbH, specializing in geospatial analytics
🎤 Community Involvement: Presented at Elixir Berlin Meetup on Bavarian Election sentiment analysis
- 🧪 Diplom-Chemiker (Chemistry) - Humboldt University Berlin (2007-2012)
- ⚡ Electrochemistry Research - 3+ years at TU Dresden & Fraunhofer IKTS (2013-2016)
- 💻 B.Sc. Computer Science - Specialization: Deep Learning, Data Mining, Computer Vision (2016-2019)
- 📈 M.Sc. Data Science - Currently pursuing (since 2022), Grade: 1.3
- Data Scientist @ Delphi IMM GmbH (2020-2025) - Geoinformation Systems, ML with satellite data
- AI Research Assistant @ Dallmeier Electronic (2018-2019) - Bachelor thesis on Neural Network optimization
- International Experience - Exchange student at Chaoyang University, Taiwan (2019-2020)
- Geospatial Analysis: QGIS, PostGIS, GeoPandas, Rasterio
- Spatial Databases: DuckDB (spatial extension), SQLite/SpatiaLite
- Machine Learning: scikit-learn, PyTorch, Computer Vision
- Data Processing: Pandas, NumPy, Dask, Apache Sedona
- Remote Sensing: Satellite imagery analysis, orthophoto processing
- Languages: Python (Advanced), C/C++ (Intermediate), Linux/Bash
- Package Management: uv, pip, conda
- Code Quality: ruff, pytest, mypy, GitHub Actions CI/CD
- Version Control: Git, GitHub, pre-commit hooks
- Documentation: LaTeX, Markdown, Hugo (Static Site Generation)
Comprehensive performance analysis of modern GIS frameworks and spatial databases
- Tech Stack: GeoPandas, DuckDB, Dask, Apache Sedona, ALKIS data
- Features: Multi-core spatial operations, memory optimization, 3.6M polygon analysis
- Research: Detailed benchmarking of overlay operations across different GIS technologies
Python library for computing clear sky sunshine duration from digital elevation models
- Tech Stack: Xarray, NumPy, DEM processing, solar radiation modeling
- Features: Shadow calculation algorithms, solar azimuth/elevation analysis
- Applications: Renewable energy assessment
Social media sentiment analysis of the 2023 Bavarian state election
- Tech Stack: Python, NLP, Mastodon API, regional differentiation
- Features: Sentiment tracking, geospatial correlation, political data analysis
- Research: Combines social media mining with regional geospatial analysis
Technical blog with automated deployment
- Live Site: sehheiden.github.io
- Tech Stack: Hugo, GitHub Actions, responsive design
- Features: CI/CD pipeline, performance optimized, SEO ready
Photovoltaic data validation using aerial image segmentation
- Research Focus: Deep Learning + Pixel-Based Image Analysis (PBIA)
- Tech Stack: PyTorch, GeoPandas, uv, ruff
- Data: German Core Energy Market Register (MaStR) + Brandenburg orthophotos
- Methods: CNNs for automated solar panel detection, geospatial validation
- 🏆 M.Sc. Data Science - Current Grade: 1.3 (≈ A- US scale)
- 🏅 Programming Competition - 3rd place at 14th Holtek Semiconductor competition (Taiwan)
- 🎤 Community Engagement - Presented at Elixir Berlin Meetup on Bavarian Election sentiment analysis
- 📚 Research Publications - Contributing to renewable energy and geospatial analysis research
- 🌏 International Experience - Exchange semester in Taiwan, Chinese language skills (HSK 3)
- 🔬 Completing M.Sc. thesis on photovoltaic data validation
- 🚀 Contributing to open-source Python geospatial tools
- 📖 Learning advanced computer vision techniques for satellite imagery
- 🌐 Building my technical blog with Hugo
- 💼 LinkedIn: Sebastian Heiden
- 🌐 Website: sehheiden.github.io
- 📧 Email: [email protected]
- 💻 GitHub: You're already here!