Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

Published on by Forensic Scientist

Assoc. Prof. Dr. Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

Samsun University | Turkey

Dr. Ozgur Tonkal is a distinguished academician and researcher at Samsun University, specializing in cybersecurity, Software-Defined Networks (SDN), and AI-driven threat detection. He earned his Ph.D. in Computer Engineering from Gazi University in 2022, where his doctoral research introduced an autonomous intrusion detection and mitigation model for SDN, providing adaptive and traffic-aware defense against volumetric attacks. Building on this foundation, he developed a multimodal spam email detection framework that integrates Distil BERT embeddings with structural features, achieving 99.62% accuracy and exposing concept drift vulnerabilities across eras of spam. Dr. Ozgur Tonkal has contributed significantly to both academic research and practical applications through international journal articles, conference papers, and book chapters that advance explainable and continually learning cybersecurity systems. His completed research includes DDoS detection using machine learning and neighborhood component analysis, while ongoing projects focus on adaptive spam detection, IoT traffic analysis, and explainable deep learning models for robust network security. Beyond academia, he serves as ISO/IEC 27001:2022 Lead Auditor, coordinator of a university Cyber Incident Response Team, and technical advisor for the Ministry of Education International Robotics Competition, demonstrating his ability to translate research into real-world solutions. Notable publications include studies on multimodal spam detection, AI-based dementia diagnosis, and DDoS attack detection in SDN. Dr. Ozgur Tonkal exemplifies excellence in research, innovation, and the practical implementation of cybersecurity solutions.

Profile: Google Scholar | ORCID | ResearchGate | LinkedIn | Staff Page

Featured Publications

  • Tonkal, Ö., Polat, H., Başaran, E., Cömert, Z., & Kocaoglu, R. (2021). Machine learning approach equipped with neighbourhood component analysis for DDoS attack detection in software-defined networking. Electronics, 10(1227), 1–18. Cited by 128.

  • Tonkal, Ö., & Polat, H. (2021). Traffic classification and comparative analysis with machine learning algorithms in software-defined networks. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 9(1), 1–12. Cited by 15.

  • Sertkaya, M. E., Ergen, B., Türkoğlu, M., & Tonkal, Ö. (2024). Accurate diagnosis of dementia and Alzheimer’s with deep network approach based on multi‐channel feature extraction and selection. International Journal of Imaging Systems and Technology, 34(3), e23079. Cited by 4.

  • Ouhsousou, S., & Tonkal, Ö. (2024). Analysis of global language dynamics: A cross-cultural examination of the most spoken languages and perceived learning ease. 8th International Artificial Intelligence and Data Processing Symposium, 1–6. Cited by 1.

  • Selimdaroğlu, Y., Yusuf, & Tonkal, Ö. (2025). Acil durum çağrı merkezi uygulamalarında kullanıcı memnuniyeti ve performans analizi: 112 örneği. International Journal of Advances in Engineering and Pure Sciences, 37(2), 45–60.

Wenbo Shen | Computer Science and Artificial Intelligence | Best Researcher Award

Published on by Forensic Scientist

Assoc. Prof. Dr. Wenbo Shen | Computer Science and Artificial Intelligence | Best Researcher Award

Zhejiang University | China

Dr. Wenbo Shen is a tenured Associate Professor at the College of Computer Science and Technology, Zhejiang University. He is a highly regarded researcher in computer software and system protection, with expertise in program analysis, operating system security, and energy-efficient system defense. With a career spanning academia and industry, Dr. Shen has established himself as an innovative scholar whose work has advanced the field of computer security on a global scale.

Professional Profile

Scopus

Google Scholar

ORCID

Education

Dr. Wenbo Shen earned his Ph.D. in Computer Science from North Carolina State University, where his dissertation focused on wireless security and physical layer signal design under the supervision of distinguished professors. Prior to this, he obtained his Bachelor of Science degree in Software Engineering from the Harbin Institute of Technology, graduating in the top tier of his class. This solid academic foundation has shaped his excellence in research and teaching.

Experience

Dr. Wenbo Shen’s professional journey reflects a balance of academic leadership and industrial innovation. He began his career as a Senior Research Scientist at Samsung Research America, where he contributed to advanced security solutions for operating systems. He later joined Zhejiang University, first as an Assistant Professor and then progressing to a tenured Associate Professor. His teaching and supervision experience has nurtured the next generation of scholars, while his leadership in funded research projects has strengthened collaborations between academia and industry.

Research Interest

Dr. Wenbo Shen’s research focuses on protecting computer software and systems through advanced program analysis techniques. His contributions span detecting software bugs in major operating systems such as Linux, FreeBSD, and Fuchsia, while also developing lightweight protection mechanisms for mobile systems, containerized environments, and edge computing. He is particularly known for creating resource- and energy-friendly defense strategies, bridging theoretical innovation with practical application in real-world computing systems.

Awards

Dr. Wenbo Shen has been recognized with multiple Distinguished Paper Awards from top international security conferences, including the European Symposium on Research in Computer Security, the Annual Computer Security Applications Conference, ACM Asia Conference on Computer and Communications Security, and the Network and Distributed System Security Symposium. These honors highlight the significance and impact of his research contributions in advancing secure computing.

Publication

Dr. Wenbo Shen has contributed extensively to high-impact journals and conferences in computer security, with his works widely cited by international researchers.

  • Title: Hypervision across worlds: Real-time kernel protection from the arm trustzone secure world
    Published on: 2014
    Citation: 400

  • Title: SKEE: A lightweight Secure Kernel-level Execution Environment for ARM
    Published on: 2016
    Citation: 126

  • Title: Ally friendly jamming: How to jam your enemy and maintain your own wireless connectivity at the same time
    Published on: 2013
    Citation: 101

  • Title: {PeX}: A permission check analysis framework for linux kernel
    Published on: 2019
    Citation: 98

  • Title: Is link signature dependable for wireless security?
    Published on: 2013
    Citation: 75

  • Title: Ptrix: Efficient hardware-assisted fuzzing for cots binary
    Published on: 2019
    Citation: 68

  • Title: NORAX: Enabling execute-only memory for COTS binaries on AArch64
    Published on: 2017
    Citation: 65

Conclusion

Dr. Wenbo Shen’s career reflects excellence in scholarship, innovation in security research, and dedication to advancing computer system protection. His pioneering contributions in operating system defense, his recognition through prestigious international awards, and his consistent high-impact publications make him a deserving nominee for the Best Researcher Award. His work continues to influence the field globally, shaping both academic research and practical applications in secure computing.