Applies rigorous scientific methods to explore, test, and validate data-driven ideas.
Spatiotemporal forecasting of regional photovoltaic production from Meteosat image sequences using a ConvLSTM model trained and evaluated against measured production and a persistence baseline.
Scientific framework for evaluating solar forecasts beyond average error metrics, using Temporal Distortion Mix and a ramp metric to assess timing errors and rapid irradiance variations.
Controlled simulator of 3D cloud scenes, generating synthetic satellite and ground-camera views to validate voxel-based reconstruction, cloud localization, and shadow prediction for solar forecasting.
Fusion of ground-based sky-camera and geostationary satellite imagery to reconstruct cloud geometry and forecast solar irradiance and cloud shadows from 10 minutes to several hours ahead.
Processing and deconvolution of SAX eddy-current signals to help engineers assess steam-generator support-plate clogging during periodic inspections.
Development and industrialization of engineer-facing software combining signal alignment, DTW, and statistical anomaly detection to prioritize atypical steam-generator inspection signals for expert review.
At the intersection of biodiversity and wind energy, this project analyzes bird behavior around turbines using camera detections and 3D radar trajectories. It examines flight movements, responses to acoustic deterrence, and links with weather and turbine operation.
