Antonello Monti

SETTer is introduced, a transformer-based model that addresses challenges of long-term multivariate time series forecasting by incorporating novel techniques for decoupled self-attention and hybrid masking and outperforms state-of-the-art models in 88% of the scenarios.

MxGPS achieves a remarkable 39% degradation under topology shifts, contrasting sharply with traditional models that can suffer up to 1400% degradation, highlighting the critical issue of topology overfitting.

A hybrid IDS for EV charging infrastructure achieves up to 99.99% accuracy in detecting network-based attacks, setting a new standard for cybersecurity in smart grids.