Author

Liana Toderean

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Aug 2026

Policy-Aware Federated Query Orchestration Across Energy Data Spaces and Edge AI Services

The execution of AI driven analytical tasks across distributed data sources and edge services remains challenging due to heterogeneous governance policies, computational constraints, and volatile edge environments. In this demonstration, we present a modular federated orchestration framework for governance-aware query...

Vasile Ofrim, Mihai Daian, Dragoș Lazea et al. · Proceedings of the VLDB Endo... · 0 citations

#artificial intelligence Preprint Sep 2026

Distributed JEPA: A Self-Supervised Framework for Energy Forecasting

A distributed Joint Embedding Predictive Architecture for self-supervised learning from heterogeneous energy time-series that predicts latent representations of masked temporal segments while integrating temporal observations and contextual information within a shared embedding space to prevent representation collapse.

Liana Toderean, T. Cioara, Vasilis Michalakopoulos et al. · 0 citations

Open access Apr 2026

Asynchronous federated learning with partial weights aggregation for energy consumption forecasting

An asynchronous federated learning framework for energy forecasting that enables continuous global model updating without waiting for all clients to complete local training is proposed and outperforms the classic FedAsync algorithm across all client groups.

Liana Toderean, Mara Mesesan, T. Cioara et al. · Science in progress · 0 citations