Hao Yan | Cyber security | Best Researcher Award

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Mr. Hao Yan | Cyber security | Best Researcher Award

Mr. Hao Yan – Phd Candidate, Harbin Institute of Technology, Shenzhen and Peng Cheng Laboratory, China.

Hao Yan is a dedicated Ph.D. candidate at the Harbin Institute of Technology (Shenzhen), where he is also affiliated with the Peng Cheng Laboratory. With a strong foundation in computer science and a keen interest in cyberspace security, he has quickly established himself in the research community. His academic path reflects a passion for innovation, particularly in the fields of graph representation learning and network intrusion detection. Hao Yan continues to make meaningful contributions to adversarial learning methodologies and cyber attack defense strategies through innovative research and collaborative projects at national and institutional levels.

Publication Profile

ORCID

🎓 Education Background

Hao Yan began his academic journey with a Bachelor’s degree from Dalian Maritime University in 2019. He then pursued and earned his Master’s degree from Tianjin University in 2022. Currently, he is working towards his Ph.D. at the School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen). His education has been consistently aligned with his focus on computer science, cyber security, and advanced AI models. His academic background provides a solid technical and theoretical base for his ongoing research endeavors in cyberspace intelligence and adversarial learning.

🏢 Professional Experience

Currently, Hao Yan is actively engaged as a Ph.D. candidate and researcher at Harbin Institute of Technology (Shenzhen) and concurrently contributes to cutting-edge research at Peng Cheng Laboratory. He is involved in several prestigious research grants, including projects under the Shenzhen Science and Technology Program, Major Key Project of PCL, and the National Natural Science Foundation of China. He has worked on research solutions that integrate industry demands, such as advanced detection systems in network security. His practical research application reflects a seamless blend of academic theory and real-world cybersecurity challenges.

🏆 Awards and Honors

While formal recognitions are under process, Hao Yan’s growing influence is demonstrated by his research’s acceptance in top databases like Scopus, Web of Science, and Ei Compendex. His work has been supported by competitive grants such as the Shenzhen Science and Technology Program and the National Natural Science Foundation of China, showing trust in his research potential. Furthermore, his pending China patent (202510907668.2) represents his commitment to innovation and technological contribution. His consistent academic performance and recognition through funded projects are clear indicators of his rising reputation in the cybersecurity research domain.

🔬 Research Focus

Hao Yan’s research expertise lies at the intersection of Graph Representation Learning, Adversarial Learning, Cybersecurity, and Network Intrusion Detection. His core innovation, the Adversarial Hierarchical-Aware Edge Attention Learning Method (AH-EAT), introduces robust edge feature representation under adversarial conditions for hierarchical detection tasks. He explores novel ways to counter advanced cyber threats and adversarial manipulation in intelligent systems. His research demonstrates how graph structures and learning models can be applied for efficient, secure, and scalable cyber defense systems, making a valuable impact on future-oriented cybersecurity frameworks.

📌 Conclusion

In summary, Hao Yan is a promising young researcher whose work addresses key cybersecurity issues through intelligent algorithms and adversarial learning frameworks. With strong academic foundations, growing publication records, institutional support, and patent contributions, Hao has established a well-defined niche in network security and AI-based detection. His contributions are paving the way for more robust, intelligent, and secure cyberspace systems, and his research trajectory shows high potential for future academic and industry breakthroughs.

📚 Top Publications 

  1. Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection
    🗓️ Published Year: 2023
    📘 Journal: Applied Sciences (ISSN: 2076-3417)
    📈 Cited by: 5 articles

  2. Graph-based Deep Learning for Intrusion Detection under Adversarial Environments
    🗓️ Published Year: 2023
    📘 Journal: IEEE Access
    📈 Cited by: 3 articles

  3. Edge-Level Graph Attention for Adversarial Robust Cyber Threat Identification
    🗓️ Published Year: 2024
    📘 Journal: Computers & Security
    📈 Cited by: 2 articles

  4. Joint Embedding and Edge Learning for Cyber Threat Modeling
    🗓️ Published Year: 2023
    📘 Journal: Soft Computing
    📈 Cited by: 1 article

  5. Adversarial Robustness in Cyber Intrusion Graph Learning
    🗓️ Published Year: 2024
    📘 Journal: ACM Transactions on Cyber-Physical Systems
    📈 Cited by: 1 article

 

Dr. Yirga Yayeh Munaye | security | Best Researcher Award

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Dr. Yirga Yayeh Munaye | secuirty | Best Researcher Award

PhD, Director of e-learning management unit, Injibara University, Ethiopia.

Dr. Yirga Yayeh Munaye is an Ethiopian academic and researcher with expertise in Electrical Engineering, Computer Science, and Information Technology. He currently serves as an Assistant Professor and Director of the E-learning Management Unit at Injibara University, Ethiopia. With a Ph.D. from National Taipei University of Technology, Taiwan, Dr. Munaye is known for his significant contributions in wireless communication, AI, and UAV-assisted resource management. His leadership in academia spans various universities, reflecting his passion for teaching, research, and community service.

Publication Profile

Google Scholar

🎓 Education Background

Dr. Munaye earned his Ph.D. in Electrical Engineering and Computer Science from National Taipei University of Technology (NTUT), Taiwan, in 2021 with a dissertation graded Excellent (91.4/100). Prior to that, he obtained an M.Sc. in Information Science from Addis Ababa University, Ethiopia, in 2014 and a B.Sc. in Information Technology from Bahir Dar University in 2009. His academic training reflects consistent excellence and specialization in advanced communication and AI applications.

👨‍🏫 Professional Experience

Dr. Munaye has served in various academic roles, including as Assistant Professor and Researcher at Injibara University since 2022, where he also coordinated postgraduate and community research services. Previously, he held teaching and research positions at Bahir Dar Institute of Technology and Assosa University. He has mentored Master’s and Ph.D. students, led network and internet chair units, and participated in proposal writing and journal editing, contributing significantly to Ethiopia’s higher education landscape.

🏆 Awards and Honors

Dr. Munaye has received numerous certificates and awards recognizing his academic contributions. These include participation in the Foundations for Excellence in Teaching Online masterclass (2023), the Science and Engineering Research training by AWB (2022), and international ICT training at XIDIAN University, China (2017). He has also earned honors for research writing, project proposal development, and higher diploma program achievements, underlining his commitment to continuous academic development.

🔬 Research Focus

Dr. Munaye’s research focuses on AI and wireless communication systems, UAV deployment strategies, mobile communications, and cybersecurity. He is especially passionate about the intersection of deep learning with resource management in next-generation networks. His work spans across emerging technologies including IoT security, biomedical sensors, and machine learning applications, reflecting a strong interdisciplinary and future-oriented research profile.

✅ Conclusion

With a career rooted in excellence, leadership, and innovation, Dr. Yirga Yayeh Munaye exemplifies the qualities of a modern researcher and educator. His contributions to teaching, mentoring, and groundbreaking research continue to make a lasting impact on Ethiopian academia and global knowledge systems.

📚 Top Publications Notes

  1. Cyber security: State of the art, challenges and future directions
    Cyber Security and Applications, 2024
    Cited by: 184

  2. UAV positioning for throughput maximization using deep learning approaches
    Sensors, 2019
    Cited by: 60

  3. An indoor and outdoor positioning using a hybrid of support vector machine and deep neural network algorithms
    Journal of Sensors, 2018
    Cited by: 58

  4. Applying Deep Neural Network (DNN) for large-scale indoor localization using feed-forward neural network (FFNN) algorithm
    IEEE ICASI Conference Proceedings, 2018
    Cited by: 38

  5. Big data: security issues, challenges and future scope
    International Journal of Computer Engineering & Technology, 2016
    Cited by: 37

  6. Deep-reinforcement-learning-based drone base station deployment for wireless communication services
    IEEE Internet of Things Journal, 2022
    Cited by: 33

  7. Indoor localization using K-nearest neighbor and artificial neural network back propagation algorithms
    WOCC Conference Proceedings, 2018
    Cited by: 33

  8. Convolutional neural networks and histogram-oriented gradients: a hybrid approach for automatic mango disease detection and classification
    International Journal of Information Technology, 2024
    Cited by: 32

 

Mr. Yifan Zhang | Cybersecurity | Best Researcher Award

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Mr. Yifan Zhang | Cybersecurity | Best Researcher Award

Postgraduate, College of Electronic Engineering, National University of Defense Technology, China

Zhang Yifan is a dynamic and accomplished Master’s student in Computer Science at the National University of Defense Technology (NUDT), China. With a rich blend of academic excellence, innovative research, national-level recognition, and artistic talent, Zhang has demonstrated outstanding leadership and scholarly achievements. He is currently engaged as a researcher at the College of Electronic Engineering, contributing significantly to national-level projects and fostering innovation in network protocol fuzzing and large language model applications.

Publication Profile

ORCID

Education Background 🎓

Zhang Yifan is pursuing a Master’s degree in Computer Science from NUDT. His academic journey has been marked by consistent top performance, including being the top-ranked candidate for graduate school admission in 2023. He has also participated in prestigious programs such as the “International Innovative Talents Training Program” and served as a Chinese Youth Representative in the Ministry of Defense International Student Technology Week.

Professional Experience 💼

Yifan has served in various impactful roles, including as a teacher and teaching assistant at Lizko International Education Investment Management Co., Ltd., where he earned accolades like “Teaching Leader” and “Most Popular Teacher.” Additionally, he was a dance instructor at Hangwu Dance School, where he led students to win 266 provincial and municipal awards. He also interned at a national-level central government agency and currently works as a researcher at a key laboratory in NUDT, where he has led multiple national innovation and entrepreneurship projects.

Awards and Honors 🏆

Zhang Yifan’s accolades include the 2024 “Challenge Cup” Academic Competition First Place & Grand Prize, multiple “FLTRP Cup” English contest grand prizes, and the 2020 Mathematical Contest in Modeling: International Meritorious Winner Prize. He has received the First Prize Scholarship and was honored as a “Merit Student” consistently from 2019–2024. He also won a Bronze Award in the 2022 International “Internet+” Innovation and Entrepreneurship Competition. His creativity and performance extend to the arts, winning first prizes in national and provincial piano and dance competitions.

Research Focus 🔬

Yifan’s research interests lie in computer science, particularly in cybersecurity, network protocol fuzzing, and the integration of large language models for state-handling methods. He has published internationally as a first author and led innovation projects recognized at national conferences. His 2025 journal article introduces a cutting-edge approach to protocol fuzzing using large language models.

Conclusion 🌟

Zhang Yifan is a multifaceted individual who excels in research, leadership, education, and the arts. With a proven track record in innovation, national representation, and academic brilliance, he is set to make a meaningful impact in the field of computer science and beyond.

📚 Publication Top Note

StatePre: A Large Language Model-Based State-Handling Method for Network Protocol Fuzzing
Published: May 2025
Journal: Electronics
 Cited by: Citations will appear on databases like Google Scholar or Scopus once indexed

Murad Njoum | CyberSecurity | Cybersecurity Achievement Award

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Dr. Murad Njoum | CyberSecurity | Cybersecurity Achievement Award

Lecturer, BirZeit University, Palestine, State of

📘 Murad Subhi Njoum is a dedicated lecturer in the Computer Science Department at Birzeit University, known for his expertise in data structures, Java programming, and cybersecurity. With over a decade of teaching experience, he has developed courses that engage students in programming and foundational computer science concepts. Murad is currently pursuing a Ph.D. in Computer Science at UKM, Malaysia, where he specializes in the field of steganography within cybersecurity, having published several papers that contribute to advancements in data security.

Publication Profile

Google Scholar

Education:

🎓 Murad holds a Master’s degree in Scientific Computing with a focus on Computer Science, graduating with distinction. His academic journey continues as a Ph.D. candidate at Universiti Kebangsaan Malaysia (UKM), Malaysia, where he expands his research on steganography and data security.

Experience:

👨‍🏫 With over ten years of teaching experience, Murad has instructed courses in data structures, Java programming, and cybersecurity, and has provided foundational knowledge in Linux, C programming, and introductory computer science. His role at Birzeit University allows him to contribute to the academic growth of his students while fostering a collaborative learning environment.

Research Focus:

🔍 Murad’s primary research focus lies in steganography within cybersecurity, exploring innovative techniques for enhancing data security. His ongoing research aims to develop new methods that improve the reliability and security of steganographic techniques, contributing to the broader field of secure information technology.

Awards and Honors:

🏆 Throughout his career, Murad has achieved significant recognition in the academic field, notably for his contributions to cybersecurity and education. He continues to strive for excellence in both research and teaching.

Publication Top Notes:

“Steganographic Techniques in Secure Data Transmission,” Journal of Information Security, 2021, focusing on improved data concealment methodologies. Cited by various articles in the field for its technical advancement in data security.

“Applications of Steganography in Cybersecurity,” Cybersecurity Journal, 2022, discussing practical implementations of steganography for enhanced data protection. Recognized widely for its relevance to practical applications in secure data handling.

“Innovations in Data Concealment Using Steganographic Methods,” Security and Data Privacy, 2023, detailing advancements in steganography. Cited frequently for its contributions to modern steganographic applications and data privacy measures.

 

Zongbao Jiang | Cybersecurity | Best Researcher Award

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Mr. Zongbao Jiang | Cybersecurity | Best Researcher Award

Under postgraduate, Engineering University of People’s Armed Police, China

📘 Zongbao Jiang is an emerging researcher specializing in computer technology at the Engineering University of People’s Armed Police. His research focuses on reversible data hiding techniques, aiming to improve embedding capacity, security, and applicability. Through innovative methods, Jiang enhances data hiding performance, ensuring the integrity and confidentiality of original content. Actively collaborating with peers and participating in workshops, he stays abreast of the latest advancements in his field.

Profile

Scopus

 

🎓 Education:

Zongbao Jiang is currently an undergraduate at the Engineering University of People’s Armed Police, where he delves into computer technology and data security. His academic journey is marked by rigorous research and a strong foundation in information security.

💼 Experience:

Zongbao Jiang has participated in a project funded by the National Natural Science Foundation of China, collaborating with notable researchers like Minqing Zhang. He has successfully published papers in top-tier journals and conferences, demonstrating his expertise and contribution to the field of computer technology.

🔬 Research Interests:

Zongbao Jiang’s research interests revolve around information security and reversible data hiding techniques. His work focuses on enhancing performance metrics such as embedding capacity and security while maintaining the confidentiality of original content. Jiang’s innovative approach aims to develop robust solutions for secure communications and data preservation.

🏆 Awards:

Zongbao Jiang has made significant contributions to his field, evidenced by his publications in high-impact journals and conferences. He holds three authorized software copyrights and has a patent under review. His work in reversible data hiding techniques has earned him recognition in the academic community.

Publications

Reversible Data Hiding Algorithm in Encrypted Images Based on Adaptive Median Edge Detection and Matrix-Based Secret Sharing
Link to article
Reversible Data Hiding in Encrypted Images based on Classic McEliece Cryptosystem
Link to article
Reversible Data Hiding Algorithm in Encrypted Domain Based on Matrix Secret Sharing
Link to article