The power grid is the largest machine humans have ever built, and it is being rebuilt right now. Electrification, intermittent renewables, and datacenter load are stressing infrastructure that was designed for a slower world. That is the problem I have organised my education and my work around.
I'm studying Sustainable Energy Engineering at KTH in Stockholm, graduating in June 2027. From 2024 to 2026 I worked alongside my studies as a Project Engineer at Ellevio, one of Sweden's largest electricity distribution companies, where I built forecasting models and BI tools that helped the business see what the grid is doing and what it will do next. Working inside a DSO taught me something no course could. The bottleneck in the energy transition is rarely the hardware. It is how well you can predict, plan, and decide with the data you already have.
That conviction pulled me toward the AI side of the problem. At the KTH AI Society I run business development, building partnerships with Google, Microsoft, AWS, and Nordic AI startups. The work connects the people training models with the people who have real problems to point them at.
The projects below are where these two worlds meet. They run on real energy data, in live systems, with software that explains what is happening rather than only displaying it.