Alea
Nondum

Alea Nondum is a personal applied laboratory for turning forecasting ideas into a running system: ingesting market and weather data, producing forecasts, storing results cleanly, and presenting them in a simple public interface.

The project is deliberately end-to-end. It is not only about the model, but also about the engineering patterns needed to operate a forecasting workflow continuously and make its output inspectable.

It is also an experiment in AI-assisted engineering, but not a vibe-coding project. Part of the motivation is to explore the practical trade-off between delegating work to AI tools and remaining in the driving seat: building and deploying faster without giving up architectural ownership, code understanding, or the learning experience.

Dr. Raffaele G. Sgarlato

Energy Software & Machine Learning Engineer

Forecasting · Optimization

Berlin, Germany

About Me

I'm an energy software and machine learning engineer working across energy markets, forecasting, optimization, and production software. My work sits where domain understanding, mathematical modelling, and robust engineering have to meet.

Across 10+ years in the energy sector, spanning academia, consulting, and industry, I have worked both as a hands-on builder and as a leader of technical projects. That combination shapes how I approach technical work: scoping complex problems, guiding modelling and architecture decisions, coordinating delivery, and staying close enough to the implementation to understand the relevant trade-offs.

The technical core of my work sits in two closely connected areas:

  • Forecasting electricity generation, demand, and prices with models and pipelines that combine market structure, statistical methods, and machine learning.
  • Optimization of flexible energy assets through mathematical programming, stochastic optimization, and algorithmic search methods, from perfect-foresight single-revenue-stream models to operation under uncertainty and multi-market dispatch.

The projects on this site show some of that work in practice. If you are interested in working together, reach out via LinkedIn. If you are interested in battery dispatch optimization, this project may also be relevant: raffaele-sg/batteries-included.