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Published in Applied Soft Computing, 2022
In this paper, for semi-supervised learning, we propose a new framework WFRSTT, which incorporates the merits of Fuzzy Rough Sets, Tri-training, a novel noise-filtering technique bad-points, and the multi-view information. Experiment results demonstrate its effectiveness in Medical Diagnosis.
Published in IPCCC, 2025
This paper proposes a DRL based TCP congestion control framework, which caters to handle various objectives (maximize throughput, minimize latency, …) set by various applications.
Published in Under Review ICDM, 2026
Published in CIKM, 2026
The paper introduces NetSight, a model that captures global-local spatial-temporal dependencies through a data-driven fusion graph, node normalization, and multi-head attention, significantly improving network traffic forecasting accuracy.
Published in ICML, 2026
Published:
In this talk, titled “The Fundamental Models of Graph Neural Networks and Their Applications,” I will introduce recent advances in GNN foundation models and discuss their practical applications across domains including network performance optimization and data-driven system intelligence.
Data Structure and Algorithms (Undergraduate), NCSU, CS, 2023
Computer Network (Graduate), NCSU, CS, 2024
Senior Design (Undergraduate), NCSU, CS, 2025