Anticipating the future is a key concern for all actors of the energy sector. More specifically, as energy became a data-driven sector, forecasting of time-series has taken significant importance for a wide range of actors:
With the rising use of Machine Learning and Artificial Intelligence approaches, another trend is emerging: the need for explainability and transparency.
Adrien Rosen is an experienced professional in the Energy sector with demonstrated experience in commodities markets.Adrien is passionate about the fast-paced energy sector, more specifically commodity markets. He believes the energy transition will be enabled by a combination of new technologies, data valorization, renewable energies, and appropriate market designs. Adrien has a demonstrated history of working on energy markets with live market trading activity (CWE gas and power markets) and a master degree in electromechanical Engineer (energy).
With a background in physics and statistics, Pierre has built robust statistical analysis and numerical modeling skills, first in the high-energy physics academic community and then in the corporate energy sector. Besides his technical work, Pierre has produced high-quality reports (including international publications in prestigious journals) and presented talks on many occasions. At N-SIDE, Pierre led a technology suite of innovative algorithms for energy price & volume forecasts and brought breakthroughs in the field of Explainable AI (XAI) to increase interpretability of trained models.