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Jia Zhang

Inaugural Robert H. Dedman Jr. Endowed Department Chair and Professor

Southern Methodist University

United States

Research Interests

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About

Jia Zhang is a Professor and the Cruse C. and Marjorie F. Calahan Centennial Chair in Engineering at Southern Methodist University, United States. His research focuses on network traffic prediction, service representation learning, and mobile vulnerability markets. Recent articles include explorations of hybrid prediction methods using temporal convolutional networks and LSTMs, as well as deep learning frameworks for recommending web services.

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2020

Collaborators (2)

Rajkumar Buyya

Professor

University of Melbourne

AUSTRALIA

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Mengyuan Wang

Associate Professor

Beihang University

CHINA

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Jia Zhang

Research Interests

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About

Articles (24)

AI’s SOUP Recipe for Trustworthiness in the Age of Black and White

Multiperspective and Energy-Efficient Deep Learning in Edge Computing

Graph-Based Diffusion Model for Service Recommendation

Dual-GNN-Driven Cooperative Optimization for Makespan-Minimized and Large-Scale 3C Dynamic Job-Shop Scheduling

STMF: A Spatiotemporal Multimodal Fusion Model for Long-Term Water Quality Forecasting

Beyond Pattern Recognition: Teaching AI to Think Critically Before It Learns

A Novel Reciprocal Dual-Channel Preference Extraction and Refinement Network for Category-Aware Service Recommendation

Immunology for AI

Energy-Efficient and Latency-Aware Task Offloading for Industrial Cloud-Edge Systems With Heterogeneous CPUs and GPUs

Ontology-Based Semantic Reasoning for Multisource Heterogeneous Industrial Devices Using OPC UA

Evaluation and Analysis of Low-socioeconomic Student Narratives: Linguistic, Sentiment, and Topic Modeling Insights

Data-Filtered Prediction With Decomposition and Amplitude-Aware Permutation Entropy for Workload and Resource Utilization in Cloud Data Centers

Hybrid Water Quality Prediction With Multimodal Low-Rank Fusion and Localized Attention

Cost-Optimized Task Offloading for Dependent Applications in Collaborative Edge and Cloud Computing

Transformer-Based Water Quality Forecasting With Dual Patch and Trend Decomposition

Energy-Minimized Partial Computation Offloading in Satellite–Terrestrial Edge Computing Networks

Network Anomaly Detection With Stacked Sparse Shrink Variational Autoencoders and Unbalanced XGBoost

Large-Scale Water Quality Prediction With Deep Decomposition Architecture and Auto-Correlation

Long-Term Water Quality Prediction With Transformer-Based Spatial-Temporal Graph Fusion

A Hybrid Prediction Method for Realistic Network Traffic With Temporal Convolutional Network and LSTM

Learning to Build Accurate Service Representations and Visualization

MSP-RNN: Multi-Step Piecewise Recurrent Neural Network for Predicting the Tendency of Services Invocation

DLTSR: A Deep Learning Framework for Recommendation of Long-tail Web Services

Shifting to Mobile: Network-based Empirical Study of Mobile Vulnerability Market

Collaborators (2)

Rajkumar Buyya

Mengyuan Wang

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