🧠 Data Engineering • 🤖 Machine Learning • 🏗️ Software Architecture
I build data-intensive software systems at the intersection of data engineering, machine learning, and software architecture. My work is production-oriented: messy data, latency, scale, reliability, and systems that remain understandable long after the demo stops impressing people.
- 🎓 Background: Engineering Doctorate (EngD) in Data Science
- 🔬 Core interests: streaming platforms, digital twins, spatiotemporal systems, applied AI
- 🐍 Primary ecosystem: Python (open, inspectable, production-first)
My work is implementation-driven and focused on operational relevance. A central project is the design and development of an Urban Digital Twin for the City of ’s-Hertogenbosch, integrating:
- real-time streaming pipelines
- geospatial and spatiotemporal data processing
- time-series storage and analytics
- forecasting and machine-learning models
- interactive 3D visualization for exploration and decision support
The system is designed as a living platform rather than a static model. This work has been presented in academic and professional venues and continues to evolve toward real-world deployment.
My research sits at the boundary between systems engineering and data science:
- real-time and streaming analytics
- data integration and interoperability
- federated and distributed data processing
- ML deployment, evaluation, and monitoring in production
- reliability, scalability, and reproducibility of data-driven systems
Architectural choices often dominate model performance. That is where I spend my time.
I prefer systems that are:
- composable — replaceable parts, minimal lock-in
- explicit — clear interfaces and data contracts
- inspectable — debuggable without folklore
- maintainable — designed for the second year, not the second week
Complexity should be visible, not hidden.
I am an open-source practitioner, primarily within the Python ecosystem. I value clarity over cleverness and reproducibility over novelty. If a system cannot be reasoned about, it does not scale.
Through DataTwinLabs, I collaborate with public organizations and industry partners on data platforms, digital twins, and applied AI systems.
I am open to collaboration on research, engineering, and applied projects where data meets real-world systems.
- 🌐 Website: https://datatwinlabs.nl
- 💼 LinkedIn: https://www.linkedin.com/in/danielwondyifraw/
- 📄 Publications / talks: https://www.jads.nl/news/paving-the-way-for-sustainable-urban-construction/
- 📫 Contact: datatengineerd[at]outlook[dot]com