Research Overview
Our research integrates computing power systems, service intelligence, and green optimization. We study cloud–edge collaboration, user-centric QoS modeling, and reliable recommendation under practical deployment constraints.
For student recruitment and application materials, see the Team page.
Key Research Areas
User-perceived and QoS-aware scheduling across heterogeneous hub resources, with cross-domain coordination under operational constraints.
Energy-efficient allocation and low-carbon objectives validated through industry collaboration and deployable system prototypes.
Reliable service intelligence—including cold-start, federated, and multimodal recommendation—under data scarcity and privacy needs.
Clustering, QoS prediction, and behavioral analytics methods with reproducible protocols and system-level evaluation.