Yong Zhu | Policy Entity Network Analysis | Research Excellence Award

Dr. Yong Zhu | Policy Entity Network Analysis | Research Excellence Award

University of Melbourne | Australia

Dr. Yong Zhu is an emerging researcher specializing in data science, policy analysis, and computational social science, with a focus on topic modeling and intelligent data-driven decision-making. His work integrates advanced natural language processing techniques, including fine-tuned RoBERTa models, to analyze science, technology, and environmental policies. He has contributed to both conference and journal publications, including research on policy evolution and governance networks. Additionally, he has developed a topic modeling data analysis and visualization platform that supports automated analytics and visual insights. His contributions also extend to multiple academic book chapters on think tank research and evaluation. With an h-index of 1, 2 documents, and 1 citation, his profile reflects early-stage yet promising contributions to data-driven policy research and analytical systems development.

Citation Metrics (Scopus)

54

3

2

0

Citations
1

h-index
1

Documents
2

Citations

h-index

Documents


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Chuan Zhang | Network Resilience and Robustness | Best Researcher Award

Prof. Chuan Zhang | Network Resilience and Robustness | Best Researcher Award

Qufu Normal University | China

Prof. Chuan Zhang is a prominent researcher in control systems, nonlinear dynamics, and multi-agent systems, with a strong academic impact reflected by an h-index of 17, 75 publications, and 1,478 citations across 1,079 documents. His research focuses on advanced control strategies for complex dynamical systems, including partial differential equation (PDE)-based systems, neural networks, and fuzzy systems under cyber-physical constraints. He has made significant contributions to event-triggered control, secure consensus, and fault-tolerant mechanisms in the presence of time delays, data compression, and cyberattacks. His work also explores synchronization of reaction-diffusion neural networks and distributed parameter systems using intelligent and adaptive control techniques. Through integrating artificial intelligence with control theory, his research enhances system resilience, stability, and efficiency, supporting applications in industrial automation, networked systems, and intelligent cyber-physical infrastructures.

Citation Metrics (Scopus)

1500

1000

500

0

Citations
1,478

h-index
17

Documents
75

Citations

h-index

Documents


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Hybrid Event-Triggered Fuzzy Secure Consensus for PDE-Based Multiagent Systems with Time Delays and Multiple Attacks
– IEEE Transactions on Automation Science and Engineering, 2026 (IF: 6.4, Q1)

Jie Hui Ng | Traffic Big Data Mining and Analysis | Network Science Excellence Award

Mr. Jie Hui Ng | Traffic Big Data Mining and Analysis | Network Science Excellence Award

Tsinghua University | Malaysia

Mr. Jie Hui Ng is an emerging researcher specializing in traffic big data mining, network analysis, and travel behavior modeling, with a growing scholarly impact reflected through his h-index, document count, and citation metrics. His research focuses on leveraging sparse data environments to extract meaningful mobility insights, particularly through advanced data-driven frameworks. His notable work, TravelForest, introduces a trajectory reconstruction and travel path selection framework using sparse license plate recognition (LPR) data, integrating road network topology and dynamic traffic conditions. By extending the random forest model with an interpretable structure, his approach achieves high accuracy and robustness under limited data availability. His contributions also reveal key determinants of route choice, such as turn frequency and data coverage, while supporting scalable, real-time traffic analysis. Furthermore, his research advances proactive traffic signal control optimization, enhancing intelligent transportation systems and urban mobility efficiency.

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