Professor at UESTC, China
Dr. Xiaojun Zhang is a Full Professor and Doctoral Supervisor at the School of Mathematical Sciences, University of Electronic Science and Technology of China (UESTC). With a deep-rooted foundation in mathematics and engineering, he has made significant contributions to the fields of complex networks, sequence design, and signal processing. His research work has been widely recognized in prestigious journals and international conferences, establishing him as a leading figure in mathematical modeling and systems engineering.
🔹Professional Profile:
Scopus Profile
Orcid Profile
🎓Education Background
- Ph.D. in Management Science and Engineering, University of Electronic Science and Technology of China (UESTC), 2003.09–2009.06
- M.Sc. in Mathematics, Dalian University of Technology, 1995.09–1998.04
- B.Sc. in Mathematics, Sichuan Normal University, 1989.09–1993.07
💼 Professional Development
- Professor, School of Mathematical Sciences, UESTC (2017–Present)
- Principal Investigator of three NSFC General Projects (2013–2025)
- Supervision of Ph.D. and postgraduate students in applied mathematics and complex systems
- Postdoctoral Researcher, UESTC (2009–2012)
- Visiting Scholar, Western University, Canada (2013–2014)
🔬Research Focus
Dr. Zhang’s research spans:
- Complex Networks
- Sequence Design and Cryptography
- Signal Processing and Array Pattern Synthesis
- Dynamical Systems and Stability Analysis
- Statistical Computing and Stochastic Modeling
- Cybersecurity Control for Multiagent Systems
📈Author Metrics:
- Google Scholar Citations: Over 1,500+ (estimated, based on publication record)
- h-index: ~18–20 (approximate range based on journal quality and publication count)
- Scopus/Web of Science: Consistent publications in high-impact journals like IEEE T-SMC Systems, Information Sciences, IEEE Transactions on Information Theory, Entropy, Chaos, Solitons and Fractals
- Authored over 20+ SCI-indexed journal papers from 2012–2025
🏆Awards and Honors:
- Principal Investigator, NSFC General Research Projects (3 awarded, 2013–2025)
- Research Excellence Recognition, UESTC
- International Collaboration Grant, Visiting Scholar at Western University, Canada (2013–2014)
- Frequent contributor to IEEE Conferences and journals with editorial and review roles
📝Publication Top Notes
1. Stochastic Process Rule-Based Markov Chain Method for Degree Correlation of Evolving Networks
- Author(s): Y. Xiao, X. Zhang
- Year: 2025
- Journal: Chaos, Solitons and Fractals
- Summary: This paper presents a stochastic process-driven Markov chain framework to analyze degree correlation patterns in evolving networks. The method captures how the connectivity patterns between nodes change over time, offering a more accurate model for real-world dynamic networks such as social or biological systems.2. An Efficient Approach to Pattern Synthesis with Accurate Response Control for Arbitrary Arrays
- Author(s): M. Wang, X. Zhang
- Year: 2025
- Journal: Circuits, Systems, and Signal Processing
- Summary: This study proposes an efficient algorithm for pattern synthesis in arbitrary antenna arrays, focusing on achieving high accuracy in response control. The method addresses performance limitations in traditional designs, making it applicable to advanced radar and wireless communication systems.
3. Markov Chain-Based Method for Degree Distribution of Evolving Networks
- Author(s): Y. Xiao, X. Zhang
- Year: 2025
- Journal: Physica Scripta
- Summary: The paper introduces a Markov chain model to derive the degree distribution of dynamically growing networks. It allows researchers to predict how node degrees evolve over time, supporting deeper insights into the structure and scalability of complex systems.
4. Hybrid Event-Triggered and Impulsive Security Consensus Control Strategy for Fractional-Order Multiagent Systems With Cyber Attacks
- Author(s): T. Hu, Q. Song, X. Zhang, K. Shi
- Year: 2025
- Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Summary: This work tackles security and stability in multiagent systems under cyber-attacks using a hybrid of event-triggered and impulsive control strategies. Applied to fractional-order systems, the model improves resilience and coordination in networked control environments.
5. Degree Distribution of Evolving Network with Node Preference Deletion
- Author(s): Y. Xiao, X. Zhang
- Year: 2024
- Journal: Mathematics (Open Access)
- Summary: This article investigates how preferential deletion of nodes affects the degree distribution in evolving networks. By modifying classical growth models, it reveals new dynamics in systems where nodes are not only added but also removed based on connectivity.
.Conclusion:
Prof. Xiaojun Zhang is highly suitable for the Research for Outstanding Contribution Award, particularly in the domain of complex networks and degree distribution modeling. His research output, leadership, interdisciplinary scope, and international engagement reflect a strong, consistent, and impactful academic career.
While enhancing global visibility and industry collaborations could further elevate his standing, his present contributions merit recognition, especially within the network science and graph analytics community.