Mr. Yixiang Zhang | Cybersecurity | Best Researcher Award

Yixiang Zhang | Cybersecurity | Best Researcher Award

Yixiang Zhang, Huazhong University of Science and Technology, China

Zhang Yixiang 🎓 is a passionate researcher in cybersecurity, backend systems, and large language models (LLMs). A CPC member 🇨🇳 and top-ranking postgraduate student at Huazhong University of Science and Technology 🏫, he combines academic excellence with strong practical experience. He has led innovative R&D efforts in open-source algorithm evaluation, security assessments, and intelligent penetration testing 🤖. Zhang is skilled in Python, C++, LangChain, and vLLM, and has earned top national honors 🏆 for his contributions. With a curious mindset, strong adaptability, and a solid foundation in machine learning and security, he aims to solve complex challenges in cyberspace security 🔐.

Professional profile :

Orcid

Suitability for Best Researcher Award :

Zhang Yixiang exemplifies the qualities of a top-tier early-career researcher in the fields of cybersecurity,backend systems, and large language models (LLMs). As a top-ranking postgraduate student at Huazhong University of Science and Technology and a member of the Communist Party of China (CPC), he has demonstrated both academic excellence and a commitment to national scientific advancement. His profile reflects a strong blend of theoretical knowledge, technical innovation, and real-world impact, which are key attributes sought in a Best Researcher Award recipient.

Education & Experience :

🎓 Education:

  • 🏫 Huazhong University of Science and Technology (2023–2026)
    Master’s in Cyberspace Security | Top 25% | Advisor: Prof. Fu Cai
    🏅 First-Class Scholarship | 🏆 “Challenge Cup” National Winner

  • 🏫 Zhengzhou University (2019–2023)
    Bachelor’s in Information Security | Top 5%
    🏅 National Endeavor Scholarship | 🏅 First-Class Scholarship
    👨‍🎓 Outstanding Student & Youth League Cadre

💼 Experience:

  • 🧠 Open Source Algorithm Evaluation Engineer, Wuhan Jinyinhu Lab (2024–2025)
    🛠️ Platform Design | 📊 Document Optimization | 🧭 Strategic Planning

  • 💻 Backend Engineer, Institute of Software, Chinese Academy of Sciences (2024–2025)
    📐 Security Evaluation | 📄 Readability Modeling | 🧪 Standard Development

Professional Development :

Zhang Yixiang continues to evolve professionally through hands-on R&D projects in cybersecurity, backend infrastructure, and open-source intelligence 🧠. He has contributed to national-level platforms and collaborated with leading institutions like the Chinese Academy of Sciences 🏢. Proficient in LLM development frameworks like LangChain and vLLM, he actively refines models for risk detection, software component analysis, and AI-driven security auditing 🔍. His commitment to practical innovation is matched by academic rigor, with one patent filed and a top-tier journal paper under review 📄. Zhang thrives in fast-paced environments, always seeking to bridge cutting-edge tech with real-world security applications 🌐.

Research Focus :

Zhang Yixiang’s research centers around cyberspace security, LLM applications, and AI-driven algorithm optimization 🔐🤖. His projects include developing penetration testing frameworks, secure open-source evaluation platforms, and advanced detection algorithms for binary code analysis 🧬. He combines multi-agent systems and retrieval-augmented generation (RAG) architectures to improve automation and decision-making in security systems 🤝. His approach integrates deep learning methods, such as LSTM and PSO-optimized random forests, with practical applications like DDoS detection and open-source risk analysis 📊. Zhang’s interdisciplinary research bridges backend engineering, AI model fine-tuning, and cybersecurity intelligence to tackle complex, real-world digital threats 🚨.

Awards & Honors :

  • 🥇 First Prize, National “Challenge Cup” Innovation Competition (2024)

  • 🥇 First Prize, Challenge Cup – Special Project Division (2024)

  • 🥇 First Prize, 15th Provincial Computer Design Competition (2022)

  • 🥈 Second Prize, ICM/MCM U.S. Mathematical Modeling Competition (2021)

  • 🥉 Third Prize, APMCM Asia-Pacific Modeling Contest (2020)

  • 🏅 First-Class Academic Scholarship (2023, 2022)

  • 🏅 National Endeavor Scholarship (Zhengzhou University)

  • 🏅 Excellent Student Leader & Youth League Cadre

Publication Top Notes : 

Title: BinCoFer: Three-stage purification for effective C/C++ binary third-party library detection

Journal of Systems and Software, May 2025
DOI: 10.1016/j.jss.2025.112480
ISSN: 0164-1212

Citation (APA Style):
Zou, Y., Z., Y., Zhao, G., Wu, Y., Shen, S., & Fu, C. (2025). BinCoFer: Three-stage purification for effective C/C++ binary third-party library detection. Journal of Systems and Software, 112480. https://doi.org/10.1016/j.jss.2025.112480

Conclusion :

Zhang Yixiang stands out as a forward-looking, innovative researcher whose work aligns closely with the mission of the Best Researcher Award—to recognize exceptional contributions that advance scientific understanding and practical impact. His achievements in cybersecurity and LLM integration, combined with national recognition and hands-on leadership in cutting-edge projects, make him a compelling nominee. His trajectory suggests continued excellence and influential contributions to the field, justifying his selection for this prestigious honor.

Dr. Shuhao Shen | Cybersecurity | Best Researcher Award

Shuhao Shen | Cybersecurity | Best Researcher Award

Shuhao Shen, Huazhong University of Science and Technology, China

Shuhao Shen is a dedicated Ph.D. student in Cyberspace Security at Huazhong University of Science and Technology (HUST) 🎓. As a member of Professor Cai Fu’s team, he focuses on cutting-edge areas such as binary vulnerability detection, graph neural networks (GNNs), and large language model (LLM) applications 🤖. Shuhao ranks in the top 25% of his Ph.D. cohort and previously ranked 12th during his undergraduate studies. He has contributed to national-level cybersecurity projects and collaborated with QiAnXin Group on binary component analysis 🛡️. Known for his diligence, curiosity, and adaptability, Shuhao aspires to lead in cybersecurity innovation 🚀.

Professional profile :

Orcid

Suitability for Best Researcher Award :

Shuhao Shen is a promising Ph.D. researcher at Huazhong University of Science and Technology (HUST), actively contributing to the fields of binary vulnerability detection, graph neural networks (GNNs), and large language model (LLM) applications. His work addresses some of the most pressing challenges in cybersecurity, including the secure analysis of binary components—an area critical to national infrastructure and digital defense. His academic performance, demonstrated by being in the top 25% of his Ph.D. cohort and previously ranking 12th in his undergraduate class, reflects consistent excellence and intellectual rigor.

Education & Experience :

🎓 Ph.D. in Cyberspace Security — Huazhong University of Science and Technology (HUST)
📍 Wuhan, China | ⏳ Sep 2023 – Jun 2028 (Expected)

  • 🧑‍🏫 Under Prof. Cai Fu’s supervision

  • 🏅 Top 25% in academic ranking

  • 🎖️ First-Class Academic Scholarship (2023)

🎓 Bachelor’s in Cyberspace Security — HUST
📍 Wuhan, China | ⏳ Sep 2020 – Jun 2024 (Expected)

  • 🏅 Ranked 12th in major

  • 🏆 Honors: Outstanding Student Cadre, Excellent Communist Youth League Cadre

💼 Algorithm Engineer Intern — Wuhan CGCL Lab
📍 Wuhan, China | ⏳ Jul 2023 – Dec 2024

  • 🔍 Focus on graph neural networks and binary vulnerability detection

  • 🤝 Collaboration with QiAnXin Group and national-level LLM projects

Professional Development :

Shuhao Shen has developed strong skills in Python 🐍 and C++ 💻, mastering deep learning frameworks and tools like LangChain and vLLM for large model deployment. He’s proficient with vulnerability detection tools such as angr 🛠️ and IDA Pro 🧠, allowing him to design efficient rule-based and AI-assisted detection schemes. His hands-on experience includes publishing in the Journal of Systems and Software and contributing to significant projects involving binary analysis 🔬, function embedding, and open-source component recognition 🧩. Shuhao’s balanced skill set and real-world project exposure position him for continued growth in advanced cybersecurity development 🔐.

Research Focus :

Shuhao Shen’s research is centered on cyberspace security 🔐, particularly in binary vulnerability detection, graph neural networks (GNNs) 🌐, and large language models (LLMs) 🤖 for software analysis. His recent work includes utilizing angr and IDA Pro for binary feature extraction and applying function embeddings for open-source component detection in C/C++ binaries 🧩. He is actively exploring the intersection of machine learning and cybersecurity, aiming to create intelligent, automated vulnerability detection systems 🔍. His research aligns with next-generation software supply chain protection, secure development environments, and AI-augmented security tools 🚀.

Awards & Honors :

🏆 National First Prize – Undergraduate Innovation and Entrepreneurship Program (Nov 2023)
🎖️ First-Class Academic Scholarship – HUST (2023)
🎓 Outstanding Student Cadre – HUST
📣 Excellent Communist Youth League Cadre – HUST

Publication Top Notes : 

TitleBinCoFer: Three-stage purification for effective C/C++ binary third-party library detection

Author: Shuhao Shen
Publication Type: Journal article
Citation (placeholder): Shen, S. (Year). BinCoFer: Three-stage purification for effective C/C++ binary third-party library detection. Journal Name, Volume(Issue), pages. DOI

Conclusion :

Shuhao Shen demonstrates the research depth, technical innovation, and real-world impact that align perfectly with the goals of the Best Researcher Award. His advanced work in cybersecurity, particularly in leveraging AI to tackle binary vulnerabilities, is not only timely but also critical in an era of escalating digital threats. Given his contributions to both academic and industrial spheres, Shuhao is well-positioned to become a future leader in cybersecurity research, making him a highly deserving candidate for this recognition.

Assoc. Prof. Dr. Shankar Karuppayah | Cybersecurity | Best Researcher Award

Shankar Karuppayah | Cybersecurity | Best Researcher Award

Shankar Karuppayah, Cybersecurity Research Centre, Malaysia

Shankar Karuppayah 👨‍💻 is a distinguished Associate Professor and Deputy Director at the Cybersecurity Research Centre (CYRES), Universiti Sains Malaysia 🇲🇾. His academic journey includes a PhD in Cyber Security from Technische Universität Darmstadt 🇩🇪, focusing on advanced P2P botnet monitoring 🕵️. Shankar’s professional experience spans roles as Senior Lecturer at NAv6, Area Head and Postdoctoral Researcher at TU Darmstadt 🇩🇪. He actively contributes to the cybersecurity community as Co-Chair of APAN’s Security Working Group 🌐 and Deputy Head of MyREN’s Internet Security Working Group 🇲🇾. His dedication to research and industry collaboration makes him a valuable asset in the field 🚀.

Professional profile :

Google Scholar

Summary of Suitability :

Shankar demonstrates a compelling profile as a researcher with a strong academic foundation, significant contributions to the field of cybersecurity and P2P networks, active engagement in the research community, and a commitment to knowledge dissemination and practical application. His international experience, leadership role, and dedication to bridging academia and industry further strengthen his suitability for such an award.

Strengths:
    • Strong Academic Foundation and Expertise: Holding a PhD in Cyber Security from a reputable international institution (Technische Universität Darmstadt) establishes a solid base of knowledge and research capabilities. His specific expertise in cybersecurity and P2P networks indicates a focused and in-depth understanding of critical areas.
    • Significant Research Contributions: Publications in numerous esteemed journals signify a consistent and impactful research output, contributing to the body of knowledge in his field.
    • Leadership and Direction: His role as Associate Professor and Deputy Director at the Cybersecurity Research Centre (CYRES) at Universiti Sains Malaysia highlights his leadership capabilities in shaping research direction and fostering a research environment.
    • International Research Experience: His time at the Telecooperation Lab in Germany demonstrates exposure to diverse research environments and collaborations, enriching his perspective and network.
    • Active Engagement in Professional Communities: Involvement in organizations like APAN and IEEE showcases his commitment to the broader research community, knowledge sharing, and staying abreast of the latest developments.
    • Dedication to Knowledge Transfer and Impact: His active involvement in fostering cybersecurity awareness and bridging the gap between academia and industry through consultancy projects indicates a commitment to translating research into practical applications and societal benefit.

Education :

  • PhD, Cyber Security, Technische Universität Darmstadt, Germany 🇩🇪
  • MSc, Software Systems Engineering, King Mongkut’s Univ. of Tech. North Bangkok, Thailand 🇹🇭
  • BSc (Hons), Computer Science, Universiti Sains Malaysia, Malaysia 🇲🇾

Experience :

  • Associate Professor, Cybersecurity Research Centre (CYRES), USM 🇲🇾 (Oct’24–present)
  • Deputy Director, Cybersecurity Research Centre (CYRES), USM 🇲🇾 (2023–present)
  • Senior Lecturer, National Advanced IPv6 Centre (NAv6), USM 🇲🇾 (2016–Sept’24)
  • Area Head, Telecooperation Lab (TK), TU Darmstadt 🇩🇪 (2020–2021)
  • Postdoctoral Researcher, Telecooperation Lab (TK), TU Darmstadt 🇩🇪 (2019–2021)

Professional Development :

Dr. Karuppayah actively engages in the cybersecurity community through memberships in APAN, IEEE, MyREN, and MBOT 🌐. His role as a journal reviewer for esteemed publications like ACM CSUR and IEEE T-IFS showcases his commitment to advancing the field ✍️. He has also contributed to USM as a Mobile Access Coordinator and Industry Liaison Fellow, and as a Subject Matter Expert for their Cyber Security Awareness Program 🛡️. His involvement in various consultancy projects, such as the Embedded Systems Upskilling Program 🛠️, highlights his dedication to bridging academic knowledge with industry needs and fostering talent in the tech sector 🌱.

Research Focus :

Dr. Karuppayah’s research primarily centers on the critical domain of cybersecurity 🛡️, with a strong emphasis on network security and threat intelligence. His work delves into the advanced monitoring and detection of peer-to-peer (P2P) botnets 🤖, exploring novel methodologies to identify and counter these malicious networks. He also investigates security challenges and solutions within the Internet of Things (IoT) 🌐 and cyber-physical systems, addressing vulnerabilities in interconnected environments. Furthermore, his research extends to the design and development of security operation center as a service (SOCaaS) solutions ☁️ and user-mobility optimized routing protocols for disaster communication networks 🚨, demonstrating a commitment to both proactive defense and resilient infrastructure.

Publication Top Notes : 

1. Title: Taxonomy and Survey of Collaborative Intrusion Detection
Citation:
Vasilomanolakis, E., Karuppayah, S., Mühlhäuser, M., & Fischer, M. (2015). Taxonomy and survey of collaborative intrusion detection. ACM Computing Surveys (CSUR), 47(4), 1–33.
https://doi.org/10.1145/2716260

2. Title: Botnet-based Distributed Denial of Service (DDoS) Attacks on Web Servers: Classification and Art
Citation:
Alomari, E., Manickam, S., Gupta, B. B., Karuppayah, S., & Alfaris, R. (2012). Botnet-based distributed denial of service (DDoS) attacks on web servers: classification and art. arXiv preprint arXiv:1208.0403.
https://arxiv.org/abs/1208.0403

3. Title: A Review on the Role of Blockchain Technology in the Healthcare Domain
Citation:
Zubaydi, H. D., Chong, Y. W., Ko, K., Hanshi, S. M., & Karuppayah, S. (2019). A review on the role of blockchain technology in the healthcare domain. Electronics, 8(6), 679.
https://doi.org/10.3390/electronics8060679

4. Title: MQTT Vulnerabilities, Attack Vectors and Solutions in the Internet of Things (IoT)
Citation:
Hintaw, A. J., Manickam, S., Aboalmaaly, M. F., & Karuppayah, S. (2023). MQTT vulnerabilities, attack vectors and solutions in the internet of things (IoT). IETE Journal of Research, 69(6), 3368–3397.
https://doi.org/10.1080/03772063.2021.1963421

5. Title: A Honeypot-driven Cyber Incident Monitor: Lessons Learned and Steps Ahead
Citation:
Vasilomanolakis, E., Karuppayah, S., Kikiras, P., & Mühlhäuser, M. (2015). A honeypot-driven cyber incident monitor: lessons learned and steps ahead. In Proceedings of the 8th International Conference on Security of Information and Networks (SIN ’15), 21–26.
https://doi.org/10.1145/2799979.2800001

Conclusion:

Shankar Karuppayah presents a well-rounded profile indicative of a highly capable and impactful researcher. His strong academic background, significant research contributions, leadership experience, international exposure, and dedication to both the academic and practical aspects of cybersecurity make him a highly suitable candidate for a Best Researcher award. His work not only advances the field but also demonstrates a commitment to broader societal impact through awareness and industry collaboration.

Mr. Stephen Afrifa | Botnet Awards | Best Researcher Award-3213

Mr. Stephen Afrifa | Botnet Awards | Best Researcher Award

Mr. Stephen Afrifa, Tianjin University, China

Mr. Stephen Afrifa is a dedicated lecturer in the Department of Information Technology and Decision Sciences at the University of Energy and Natural Resources (UENR), with a strong background in IT project management, data science, AI, and machine learning. He holds a Master of Science in Engineering from Tianjin University, China, where his research focused on using machine learning models to assess climate change impacts. With expertise in a wide range of programming languages and statistical tools, Stephen has developed software solutions and led research initiatives in both academic and professional settings. His leadership in AMANPENE Foundation and UENR reflects his commitment to using technology for societal good, particularly in climate modeling and poverty alleviation.

Professional Profile:

Google Scholar

Orcid

Scopus

Suitability for the Award:

Mr. Stephen Afrifa is a suitable candidate for the Best Researcher Award due to his strong academic background, impactful research publications, interdisciplinary collaborations, and leadership in addressing significant societal challenges through technology and AI. His dedication to teaching, research, and community service further bolsters his eligibility, making him a distinguished candidate deserving of this award.

Educational Background

Stephen holds a Master of Science in Engineering (Information and Communication Engineering) from Tianjin University, where he focused on machine learning models related to climate change. His foundational education includes a WASSCE Certificate from Kumasi High School.

Professional Overview

Mr. Stephen Afrifa is a proactive and versatile individual with a strong commitment to enhancing user experiences through technology. He excels in both quantitative and qualitative projects and thrives in international, multicultural environments.

Work Experience

Currently a Lecturer in the Department of Information Technology and Decision Sciences at the University of Energy and Natural Resources (UENR), Stephen supervises and guides students at various academic levels. He also serves as a part-time Software Application Developer at CY Technologies, leading software development and research projects.

Skills and Expertise

Well-versed in programming languages and statistical tools like Python, R, C/C++, and more, Stephen has a robust background in IT project management, network security, and data science. His research interests include IoT, cybersecurity, and cloud computing, emphasizing sustainable practices.

Honors and Leadership

Recognized as the Best Graduating Student in Computer Science at UENR and a recipient of the Absa Tertiary Scholarship, Stephen also holds leadership roles, including being an Academic Board Member at Eterno Press and a Lead Research Facilitator at UENR.

Publication Top Notes:

  • Title: Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis
    • Year: 2022
    • Cited by: 44
  • Title: Detection of Anemia Using Conjunctiva Images: A Smartphone Application Approach
    • Year: 2023
    • Cited by: 23
  • Title: Ensemble Machine Learning Techniques for Accurate and Efficient Detection of Botnet Attacks in Connected Computers
    • Year: 2023
    • Cited by: 20
  • Title: Cyberbullying Detection on Twitter Using Natural Language Processing and Machine Learning Techniques
    • Year: 2022
    • Cited by: 16
  • Title: VAR, ARIMAX and ARIMA Models for Nowcasting Unemployment Rate in Ghana Using Google Trends
    • Year: 2023
    • Cited by: 15