Mr. Han Zhang | Network Security | Best Researcher Award

Associate Professor at Tsinghua University, China

Author Profile

Summary

Dr. Han Zhang is a Special Research Fellow and Doctoral Supervisor at the Institute for Network Sciences and Cyberspace, Tsinghua University. With a strong foundation in computer science and network security, he has cultivated a career that bridges advanced research and practical innovation in cyberspace governance and network science. His work spans interdisciplinary domains, driving impactful contributions in cybersecurity education and system-level network research. Committed to academic excellence and talent cultivation, Dr. Zhang is recognized for his mentorship and pioneering teaching reforms. He also actively leads collaborative international research, maintaining a strong presence in the global academic community.

Educational Background

Dr. Han Zhang earned his Ph.D. in Computer Science and Technology from Tsinghua University (2013.09–2018.07), under the supervision of Professor Xia Yin. During his doctoral studies, he was a visiting scholar at George Washington University (2016.10–2017.09), working with Prof. Lan Tian in the School of Electrical and Information Engineering. He holds a bachelor’s degree in Computer Science and Technology from Jilin University (2009.08–2013.06). His academic training reflects a solid grounding in both theoretical and applied aspects of computer science, forming the basis for his later work in network security and systems research.

Professional Experience

Dr. Zhang has served as a Special Research Fellow and Ph.D. advisor at the Institute for Network Sciences and Cyberspace, Tsinghua University. He was an Assistant Professor and Master’s Supervisor at the School of Cybersecurity, Beihang University. He has also led courses and supervised graduate research in programming and network security. His roles have consistently involved curriculum reform, student mentoring, and interdisciplinary research collaboration. Dr. Zhang’s academic positions reflect his commitment to both foundational research and the cultivation of next-generation cybersecurity professionals.

Research Interests

Dr. Zhang’s research interests encompass network science, cyberspace governance, system security, and cybersecurity education. His work integrates data-driven methodologies with system design to explore trust, resilience, and efficiency in networked systems. He is particularly focused on enhancing the security of critical infrastructure through intelligent algorithms and robust frameworks. Additionally, he investigates educational strategies for cultivating application-oriented cybersecurity talent. His interdisciplinary perspective positions him at the intersection of theoretical innovation and practical deployment, contributing to the strategic evolution of secure and sustainable digital ecosystems.

Author Metrics

Dr. Han Zhang has published extensively in high-impact journals and conferences in the fields of computer science and network security. He has co-authored significant teaching reform papers, including in Industrial and Information Technology Education, where he explored curriculum innovation and cybersecurity talent development. His academic work is accessible via NetSys Lab, and he has garnered increasing citations for both technical and pedagogical contributions. His collaborative and first-author papers reflect a balanced academic profile, with a growing international scholarly influence in cybersecurity education and network systems research.

Awards and Honors

Throughout his academic career, Dr. Zhang has received multiple accolades for excellence in research, teaching, and innovation. As a Party member, he actively engages in academic leadership and mentorship, contributing to institutional and national education reforms. His teaching reform initiatives have been recognized for their practical impact on developing high-caliber cybersecurity professionals. He has also led and participated in funded projects focused on network security and educational development. These honors reflect his sustained contributions to the advancement of both science and pedagogy in China’s evolving digital landscape.

Publication Top Notes

1. Centralized Network Utility Maximization with Accelerated Gradient Method

Authors: Y. Tian, Z. Wang, X. Yin, X. Shi, J. Yang, H. Zhang
Journal: IEEE Transactions on Networking
Year: 2025 (Forthcoming/Published)
Details: This paper presents a centralized algorithm using an accelerated gradient method for efficient network utility maximization, achieving faster convergence and scalable optimization for large-scale networks.

2. ACME++: A Secure Authorization Mechanism for ACME Clients in the Web PKI Ecosystem

Authors: T. Zhang, H. Zhang, Y. Wei, Y. Li, X. Shi, J. Wang, X. Yin
Conference: Proceedings of the ACM Web Conference (WWW)
Pages: 1058–1067
Year: 2025
Abstract: ACME++ strengthens the ACME protocol by introducing a novel, secure client authorization method within the Web PKI system, improving defense against client impersonation and replay attacks.

3. Poster: Scalable and Interpretable Multilayer Overlay Network Checking via Ensemble Verification

Authors: X. Liu, Y. Li, H. Zhang, X. Yin, X. Shi, Z. Wang, G. Ren, J. Yao
Conference: ACM SIGCOMM 2024 – Posters and Demos Track
Pages: 22–24
Year: 2024
Publisher: ACM
Description: This poster introduces an ensemble-based verification tool enabling scalable analysis and interpretability for multilayer overlay networks used in complex infrastructure setups.

4. Cost-efficient Flow Migration for SFC Dynamical Scheduling in Geo-distributed Clouds

Authors: W. Chen, Z. Wang, H. Zhang, X. Yin, X. Shi
Journal: Computer Networks
Volume: 249
Article Number: 110496
Year: 2024
Publisher: Elsevier
Abstract: This study introduces a dynamic, cost-optimized scheduling algorithm for service function chaining (SFC) across geographically distributed cloud environments, addressing performance and resource constraints.

5. ROV-GD: Improving the Measurement of ROV Deployment Using Graph Difference

Authors: J. He, Y. Li, H. Zhang, C. An, J. Wang
Conference: 2024 IEEE Symposium on Computers and Communications (ISCC)
Pages: 1–7
Year: 2024
Publisher: IEEE
Abstract: ROV-GD leverages graph-difference metrics to refine the measurement accuracy of Route Origin Validation (ROV) deployments, improving BGP routing security assessment.

Conclusion

Dr. Han Zhang exemplifies a modern cybersecurity researcher with a well-rounded profile in theoretical innovation, practical systems research, interdisciplinary integration, and educational reform. His affiliation with Tsinghua University, impactful publications in IEEE and ACM, and his leadership in cybersecurity education firmly establish him as a highly deserving recipient of the Best Researcher Award in Network Security.

Zubaida Rehman- IoT security

Dr. Zubaida Rehman distinguished academic and researcher in the field IoT security. The focal point of her research was to enhance energy production while minimizing wake effects, a challenge that she addressed effectively through the application of Genetic Algorithms. This comprehensive study not only deepened her understanding of cutting-edge technologies in the field but also contributed to the ongoing discourse surrounding sustainable energy solutions.

Education

From 2012 to 2015, she pursued her Master of Computer Science at the National University of Computer and Emerging Sciences in Islamabad, Pakistan. Throughout this academic journey, she specialized in various domains such as Computational Intelligence, Advanced Databases, Cloud Computing, and Evolutionary Computation. The culmination of her academic endeavors was manifested in her research thesis, where she delved into the intricate realm of the Wind Turbine Layout Optimization Problem. Employing the innovative approach of Genetic Algorithms, she endeavored to optimize the layout design by incorporating diverse turbine sizes.

Professional Profiles:

Research Interest

With a diverse set of technical skills and a keen interest in cutting-edge research, she has a strong foundation in data science, encompassing data analysis and business analytics. Her expertise extends to areas such as cybersecurity, Internet of Things (IoT), and machine learning. Adept in computational intelligence, she excels in addressing real-world optimization problems with a focus on cost-effective and efficient analyses. Her proficiency in big data management within cloud environments is demonstrated through her work on effective scheduling for incoming data stream processing.

Work Experience

Her professional journey includes roles as a Software Engineer at KN Technologies Islamabad (Part Time) from January 2016 to December 2016, where she contributed to projects developed in C, C#, and PHP, demonstrating her skills in project planning and execution. As a Software Developer at Technology Architect Islamabad from January 2014 to December 2015, she engaged in the design and testing of ongoing projects, particularly focusing on Infinite-Space Shortest Path Problems and Semicontractive Dynamic Programming.

In the academic realm, she has made notable contributions with research papers published in renowned conferences such as IEEE Conference on Cloud Computing and Big Data Analysis 2016. Her survey paper on “Survey on Branch Prediction Techniques” was published in RJIIT 2017. She has further showcased her research acumen through term papers and reviews, including topics like the automatic design of multi-objective ant colony optimization algorithms, emerging trends in cloud computing, imperfect distributed learning in traffic light control, and a survey paper on the Rapid Multi-Agent Development Toolkit. Through her extensive academic and professional background, she continues to be a valuable asset in the intersection of technology, research, and software development.

Publication