Featured Publications

Journals (selected)

• Dual-GNN-driven Cooperative Optimization for Makespan-minimized and Large-scale 3C Dynamic Job-shop Scheduling
  Authors: Jing Bi, Chen Wang, Ziqi Wang, Junqi Zhang, Haitao Yuan, Jia Zhang, Rajkumar Buyya
  IEEE Transactions on Automation Science and Engineering (TASE), 2026 [PDF]

  This work combines dual graph neural networks with cooperative optimization to reduce makespan in large-scale dynamic 3C job-shop scheduling.

• Online Workload Scheduling for Social Welfare Maximization in the Computing Continuum
  Authors: Hailiang Zhao, Ziqi Wang, Guanjie Cheng, Wenzhuo Qian, Peng Chen, Jianwei Yin, Schahram Dustdar, Shuiguang Deng
  IEEE Transactions on Services Computing (TSC), 2025 [PDF]

  This work designs online workload scheduling for computing-continuum systems to improve social welfare under uncertain request arrivals.

• Long-Term Water Quality Prediction With Transformer-Based Spatial-Temporal Graph Fusion
  Authors: Jing Bi, Ziqi Wang, Haitao Yuan, Xiangxi Wu, Renren Wu, Jia Zhang, MengChu Zhou
  IEEE Transactions on Automation Science and Engineering (TASE), 2025 [PDF]

  This work uses spatial-temporal graph fusion with transformer modeling to improve long-term water quality prediction across monitoring stations.

• STMF: A Spatio-Temporal Multimodal Fusion Model for Long-term Water Quality Forecasting
  Authors: Jing Bi, Xiangxi Wu, Haitao Yuan, Ziqi Wang, Damien Wei, Renren Wu, Jia Zhang, Junfei Qiao, Rajkumar Buyya
  IEEE Internet of Things Journal (IOTJ), 2025 [PDF]

  This work develops a spatio-temporal multimodal fusion model for more reliable long-term water quality forecasting.

• Ontology-Based Semantic Reasoning for Multisource Heterogeneous Industrial Devices Using OPC UA
  Authors: Jing Bi, Rina Wu, Haitao Yuan, Ziqi Wang, Jia Zhang, MengChu Zhou
  IEEE Internet of Things Journal (IOTJ), 2025 [PDF]

  This work uses ontology-based reasoning and OPC UA to support semantic integration across heterogeneous industrial devices.

• Hybrid Water Quality Prediction With Multimodal Low-Rank Fusion and Localized Attention
  Authors: Jing Bi, Yibo Li, Haitao Yuan, Mengyuan Wang, Ziqi Wang, Jia Zhang, MengChu Zhou
  IEEE Internet of Things Journal (IOTJ), 2025 [PDF]

  This work improves hybrid water quality prediction through multimodal low-rank fusion and localized attention mechanisms.

• Cost-Minimized Computation Offloading and User Association in Hybrid Cloud and Edge Computing
  Authors: Jing Bi, Ziqi Wang, Haitao Yuan, Jia Zhang, MengChu Zhou
  IEEE Internet of Things Journal (IOTJ), 2024 [PDF]

  This work optimizes user association and computation offloading decisions to minimize cost in hybrid cloud-edge systems.

• Large AI Models and Their Applications: Classification, Limitations, and Potential Solutions
  Authors: Jing Bi, Ziqi Wang, Haitao Yuan, Xiankun Shi, Ziyue Wang, Jia Zhang, MengChu Zhou, Rajkumar Buyya
  Software: Practice and Experience (SPE), 2024 [PDF]

  This work surveys large AI models by classifying their applications, limitations, and possible technical solutions.

• Partial and cost-minimized computation offloading in hybrid edge and cloud systems
  Authors: Haitao Yuan, Jing Bi, Ziqi Wang, Jinhong Yang, Jia Zhang
  Expert Systems with Applications (ESWA), 2024 [PDF]

  This work studies partial computation offloading strategies that reduce cost in hybrid edge-cloud computing systems.

• Hybrid Water Quality Prediction based on Attention combined with Frequency Enhancement and Multi-Seasonal Decomposition
  Authors: Yibo Li, Ziqi Wang, Haitao Yuan, Jing Bi
  Journal of Water Process Engineering (JWPE), 2025 [PDF]

  This work combines attention, frequency enhancement, and multi-seasonal decomposition for hybrid water quality prediction.

• Self-adaptive teaching-learning-based optimizer with improved RBF and sparse autoencoder for high-dimensional problems
  Authors: Jing Bi, Ziqi Wang, Haitao Yuan, Jia Zhang, MengChu Zhou
  Information Sciences (INS), 2023 [PDF]

  This work integrates adaptive teaching-learning optimization, surrogate modeling, and sparse autoencoding for high-dimensional optimization problems.

• An Enhanced Hybrid Deep Neural Network Method for Adjusted Industrial Time Series Prediction with Variable Operating States
  Authors: Meifang Zhang, Jing Bi, Haitao Yuan, Ziqi Wang, Jia Zhang, Rajkumar Buyya
  Expert Systems with Applications (ESWA), 2025 [PDF]

  This work proposes an enhanced hybrid deep neural network for industrial time series prediction under changing operating states.

• Multi-Perspective and Energy-Efficient Deep Learning in Edge Computing
  Authors: Haitao Yuan, Jing Bi, Ziqi Wang, Jia Zhang, MengChu Zhou, Rajkumar Buyya
  IEEE Internet of Things Journal (IOTJ), 2025 [PDF]

  This work reviews multi-perspective and energy-efficient deep learning methods for edge computing environments.

• Assistive Assessment of Neurological Dysfunction via Eye Movement Patterns and Ocular Biometrics
  Authors: Ziqi Wang, Jing Bi, Xiaomeng Zhao, Zhipeng Zheng, Jinglei Cui, Rong Cui, Junqi Zhang, Yuanchen Tang, Jiantao Liang, Kai Zhou, Jia Zhang
  Artificial Intelligence Surgery (AIS), 2025 [PDF]

  This work explores eye movement patterns and ocular biometrics for assistive assessment of neurological dysfunction.

• FedCAD: Federated Learning with Clustering, Adaptive Selection, and Delayed Aggregation for Heterogeneous IoT Environments
  Authors: Tian Liu, Zhiwei Ling, Ziqi Wang, Jiahui Zhai, Chenggang Shan, Zhen Yang, Bin Yang
  IEEE Internet of Things Journal (IOTJ), 2026 [PDF]

  This work improves federated learning in heterogeneous IoT environments through clustering, adaptive selection, and delayed aggregation.