Academic Profile

I am currently pursuing a Ph.D. degree in Computer Science and Technology at Beijing Normal–Hong Kong Baptist University (BNBU), under the supervision of IEEE Fellow Professor Weijia Jia. My research centers on one fundamental question: how can distributed intelligence be efficiently orchestrated across heterogeneous and dynamic edge environments? I approach this question from the perspective of edge resource management and intelligent orchestration, where computing, networking, and service resources must be jointly coordinated under constraints of latency, resource heterogeneity, dynamic workloads, and limited cross-domain information. Rather than treating deployment, scheduling, and resource allocation as isolated optimization problems, I investigate how edge systems can evolve from efficient infrastructure management toward adaptive and collaborative intelligence across the cloud–edge–end continuum.

My research therefore follows a progressive path: from managing resources at the edge, to enabling intelligence at the edge, and ultimately to coordinating intelligence from edge to end. Representative work includes container migration with layer sharing (IEEE/ACM ToN 2024), container image caching (MSN 2023), resource overbooking and scheduling (IEEE TMC 2024), and adaptive edge service management (IEEE TSC 2026). My recent and ongoing research further explores cross-domain collaboration, multi-agent decision making, and causal reasoning for distributed edge intelligence, with work appearing in or targeting venues including IEEE TMC and ACM CSUR. My long-term goal is to develop scalable, adaptive, and explainable edge intelligence systems that jointly reason about computing resources, network conditions, and user experience, bridging learning-based decision making with practical and deployable distributed systems.