Projects
A look at Medoid AI’s research collaborations and projects, applying custom AI to real-world challenges across industries.
FUTURE: Facilities for Unified Next-generation Wind Tunnel Testing and Research in Europe
A flagship Horizon Europe project expanding the testing capabilities of Europe’s leading wind tunnels, coordinated by the Royal Netherlands Aerospace Centre (NLR), with the goal of accelerating the wind tunnel testing process by 40% to enable validation of the aircraft technologies required for the climate-neutral aviation of 2040.
The consortium brings together 16 partners across 9 European countries: seven Research and Technology Organisations (NLR, DLR, CIRA, AIT, VKI, Łukasiewicz, VZLU), three wind tunnel facility providers (DNW, ETW, ONERA), five SMEs including Medoid AI contributing applied AI expertise, and one university (Technical University of Braunschweig).
Medoid AI’s role: As one of five SMEs in the consortium, Medoid AI contributes applied AI expertise to FUTURE’s AI-accelerated data analysis capabilities. Specific activities will be shared as the project progresses.
Duration: 1 June 2026 – 31 May 2030. Total budget: €15.5 million.
Funded by the European Union under Horizon Europe (Grant ID 101270147). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union.
MALENA: Machine Learning System for Energy Data Analysis and Management
MALENA equips Greece’s Public Power Corporation (PPC) with in-house forecasting tools for participation in the European Day-Ahead and Intra-Day energy markets, replacing third-party dependencies and giving consumers personalized access to their energy data.
Our research explored two approaches:
- Deep neural networks for load and renewable generation forecasting
- Multi-target prediction on structured energy and weather data
Delivered: An integrated software prototype with a web interface for load forecasting, personalized load management, and renewable energy forecasting, plus novel methods for short-term, day-ahead electricity demand and wind energy generation forecasting.
Published: 11 peer-reviewed scientific conference papers.
Co-financed by the European Regional Development Fund and Greek national funds through the RESEARCH – CREATE – INNOVATE programme (Τ2EDK-03048).
