Bart Olsthoorn
Ph.D. in Physics · Product Engineer at Flower
Now
Product engineer building software end-to-end — from data pipelines on Databricks to the APIs and web interfaces on top. At Flower that means distributed energy assets: batteries, solar, EVs, heat pumps. Building a lot with AI agents in product lately.
Experience
- 2023–now
- Flower Product Owner / Engineer · Distributed Assets · Stockholm
- 2012–2017
- Freelance ML at Similar.ai (early GANs), Ruby/Elixir at Universal Avenue, Rails at InnerBalloons & Pointer Brand Protection.
Stack
- Core
- Python, Go, full-stack web (APIs & interfaces), AWS, Databricks, PostgreSQL
- AI
- Agents and agentic loops in production · PyTorch · Pandas / NumPy / scikit-learn
- Past
- Ruby / Rails, Elixir, Swift / Objective-C
Education
- 2018–2023
- KTH Royal Institute of Technology Ph.D. Physics · thesis: Homology and machine learning for materials informatics · 11 peer-reviewed publications
- 2015–2018
- Stockholm University M.Sc. Computational Physics
Open source
Long-time open-source enthusiast — 500+ stars across repos on GitHub.
Selected publications
- Persistent homology of quantum entanglement Physical Review B, 2023 · Editors' Suggestion
- Band gap prediction for large organic crystal structures with machine learning Advanced Quantum Technologies, 2019
Full list on Google Scholar.