Day-Ahead Heat Demand Prediction Using BiLSTM-Based Hybrid Neural Networks
Proceedings of the 26th International Scientific Conference on Electric Power Engineering, Opole, Poland, 18-20 May 2026.
PhD student at the Faculty of Electrical Engineering, University of West Bohemia. I work on neural-network forecasting, day-ahead heat-demand prediction, and data-driven operational optimisation for advanced energy systems.
Research stays, workshops, internships, and training across AI-supported energy-system modelling and optimisation.
Journal article, conference papers, posters, bachelor thesis, and master thesis with direct access and clear metadata.
Public-facing energy communication and outreach projects for regions affected by coal phase-out.
The portfolio is positioned around a precise research identity: neural-network forecasting, hybrid prediction models, data-driven optimisation, and operational decision support for energy infrastructure.
Open latest publicationProceedings of the 26th International Scientific Conference on Electric Power Engineering, Opole, Poland, 18-20 May 2026.
Poster/presentation record on neural-network-based operational optimisation of small modular reactors.
Sustainable Energy Technologies and Assessments, Volume 87, March 2026, 104912.