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

Dr. Maher Alrahhal | Security | Best Researcher Award

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Dr. Maher Alrahhal | Security | Best Researcher Award

Postdoctoral, University of Sharjah, United Arab Emirates

Dr. Maher Abdul Moein Alrahhal is a Postdoctoral Research Associate at the Research Institute of Science and Engineering, University of Sharjah, UAE, and a Postdoctoral Fellow at Amity University Dubai, UAE. He holds a Ph.D. in Computer Science and Engineering from Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, specializing in Artificial Intelligence, Big Data, and Data Analysis. With a solid background in computer science and engineering, Dr. Alrahhal has made significant contributions to the fields of machine learning, image retrieval, and data mining 🌐💡.

Publication Profile

Google Scholar

🌍

🎓Education Background

Dr. Alrahhal’s educational journey is marked by excellence, with a Ph.D. in Computer Science and Engineering from JNTU, Hyderabad, India (March 2024). He completed his Master of Technology in Computer Science and Engineering with First Division from the National Institute of Technology, Warangal, India (July 2018). He holds a Bachelor’s degree in Computer Engineering from the University of Aleppo, Syria, graduating with honors and securing the first rank in his department 🏆📚.

👨‍🏫Professional Experience

Dr. Alrahhal has a robust academic career with over five years of teaching experience at prominent institutions in Syria and India. He has served as a Teaching Assistant at the University of Aleppo, and later as a Lecturer and Assistant Supervisor at JNTU, Hyderabad. Dr. Alrahhal also led the Big Data Lab at JNTU and played a key role in mentoring seven master’s students. His postdoctoral roles involve research and teaching at the University of Sharjah and Amity University Dubai, UAE 💻📖.

🛰️

🏅Awards and Honors

Dr. Alrahhal has received several prestigious awards, including the Best Paper Award at IEMTRONICS 2025 for his work on “Hybrid CNN for Efficient Content-Based Image Retrieval Cognitive Systems” 🥇. In recognition of his outstanding achievements, he was honored with the Alan Turing Award at the International Royal Golden Award ceremony (2023). Other notable accolades include the University Excellence Distinction for first-ranking in 2014 and multiple Al-Basel Certificates for Excellence 🏅🎖️.

🔍 Research Focus

Dr. Alrahhal’s research focuses on Artificial Intelligence, Machine Learning, Big Data, Data Mining, and Image Retrieval. His work explores the integration of deep learning techniques with image and video processing, multimedia systems, and the application of Hadoop for scalable data analysis. His contributions aim to advance content-based image retrieval systems and the development of intelligent systems for real-world applications 📊🤖.

💡🌐Conclusion

Dr. Maher Abdul Moein Alrahhal is a dynamic researcher and academic, committed to advancing the fields of Artificial Intelligence and Data Science. With numerous published works in high-impact journals and ongoing research initiatives, he continues to shape the future of intelligent systems and multimedia applications 🌟📈.

🔧

📚Publications

Disruptive Attacks on Artificial Neural Networks: A Systematic Review of Attack Techniques, Detection Methods, and Protection Strategies, Intelligent Systems with Applications, in press.

MapReduce model for efficient image retrieval: a Hadoop-based framework, International Journal of Information Technology (Springer, Scopus Q1).

Enhancing Image Retrieval Systems: A Comprehensive Review of Machine Learning Integration In CBIR, International Journal of Intelligent Systems and Applications in Engineering, 12(4), 4195–4214.

Integrating Machine Learning Algorithms for Robust Content-Based Image Retrieval, International Journal of Information Technology, DOI: 10.1007/s41870-024-02169-2 (Springer, Scopus Q1).

Automatic diagnosis of epileptic seizures using entropy-based features and Multimodal Deep Learning Approaches, Medical Engineering and Physics, DOI: 10.1016/j.medengphy.2024.104206, (Elsevier, Scopus Q1).

Enhancing image retrieval accuracy through multi-resolution HSV-LNP feature fusion and modified K-NN relevance feedback, International Journal of Information Technology, DOI: 10.1007/s41870-024-02000-y, (Springer, Scopus Q1).

Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

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Assoc. Prof. Dr. Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

Cybersecurity, previously at University of Central Florida in USA and now at Tikrit University in Iraq

Qutaiba Abdullah Hasan Alasad is an Associate Professor and Head of the Department of Control and Computer Engineering at the University of Tikrit, Iraq. With a Ph.D. in Computer Engineering from the University of Central Florida (UCF), USA, he has developed expertise in hardware security, particularly in the areas of logic encryption, obfuscation techniques, and secure design for emerging devices. His research work focuses on enhancing hardware protection, preventing side-channel attacks, and leveraging memory computing for secure and high-performance systems. He has also been involved in various presentations and has earned several prestigious awards for his contributions to computer engineering and cybersecurity. 📚🔒

Publication Profile

Google Scholar

Education

Dr. Alasad completed his Ph.D. in Computer Engineering from the University of Central Florida (UCF) in 2020, with a perfect GPA of 4.0/4.0. His dissertation, titled “Provably Trustworthy and Secure Hardware Design with Low Overhead,” was supervised by Prof. Yuan Jiann-Shiun. He also holds an M.Sc. in Computer Engineering from the University of Mosul, Iraq, where he designed a math pipeline processor using VHDL and implemented it on Spartan-3E. 🎓🇮🇶

Experience

Dr. Alasad has served in various prestigious positions, including the Head of the Department at the University of Tikrit’s College of Petroleum and Minerals Engineering and Dean of the College of Petroleum Systems Control Engineering. He was also involved in several roles at the University of Central Florida, where he worked under the supervision of Prof. Jiann-Shiun Yuan. His vast experience spans over teaching, research, and administrative roles. 💼👨‍🏫

Awards and Honors

Dr. Alasad has received several notable recognitions, including a Travel Award from the ICCD Conference in 2017 and a complimentary annual membership from Gabriele Kotsis, President of the ACM journal, in 2020. He has presented his research at various symposiums, covering topics such as Internet of Things (IoT) applications and power electronics systems simulation. 🏅🌍

Research Focus

Dr. Alasad’s research interests are centered around hardware security, particularly logic encryption and obfuscation techniques, side-channel attack prevention, and the application of emerging devices to enhance hardware security. He is also focused on designing secure memory systems using ReRAM and creating high-performance machine learning accelerators. Additionally, his work on big data security and cybersecurity protection based on machine learning is highly impactful in the domain. 🔐💻

Conclusion

Qutaiba Alasad’s interdisciplinary expertise and contributions to hardware security, especially in the realm of logic encryption and emerging devices, position him as a leader in the field. His academic achievements, coupled with his extensive work in cybersecurity, make him a prominent figure in the engineering community. 🏆👨‍💻

Publications

Design a Pipelined Math Processor, Doubling Its Speed and Implementing It on FPGA

Al-Rafidain Engineering Journal (AREJ), Volume 22, Issue 4, Pages 131-148, 2014

Cited by: 10+

E2LEMI: Energy-Efficient Logic Encryption Using Multiplexer Insertion

Electronics, vol. 6, issue 1, 2017

Cited by: 50+

Logic Locking Using Hybrid CMOS and Emerging SiNW FETs

Electronics, vol. 6, issue 3, 2017

Cited by: 30+

Ultra-Low-Power Design and Hardware Security Using Emerging Technologies for Internet of Things

Electronics, vol. 6, issue 3, 2017

Cited by: 40+

Logic Obfuscation against IC Reverse Engineering Attacks with Low Overhead

ACM Trans. TODAES, 2020

Cited by: 75+

Resilient and Secure Hardware Devices Using ASL

ACM journal on emerging technologies in computing systems, 2021

Cited by: 20+

Multi-Tier 3D IC Physical Design with Analytical Quadratic Partitioning Algorithm Using 2D P&R Tool

Electronics, 2021

Cited by: 15+

Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML

MDPI Computers, 2022

Cited by: 25+

Nordine Quadar | Cybersecurity | Best Researcher Award

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Mr. Nordine Quadar | Cybersecurity | Best Researcher Award

Researcher, Royal Military College of Canada, Canada

🎓 Nordine Quadar, P.Eng, is a dedicated technical manager, researcher, and educator based in Montreal, Canada. With a strong foundation in engineering and advanced expertise in cybersecurity and artificial intelligence, he specializes in leveraging cutting-edge technologies to enhance the security of UAV systems. Passionate about teaching, he has guided students through complex subjects and contributed significantly to the fields of smart grids, IoT, and machine learning.

Publication Profile

Google Scholar

Education

📚 Nordine Quadar holds a PhD in Computer Science (in progress, 2022–2025) from the Royal Military College of Canada, supervised by Abdellah Chehri, focusing on UAV cybersecurity using Edge AI. He earned a Master of Applied Science in Electrical & Computer Engineering (2015–2018) from the University of Ottawa under the supervision of Claude D’Amours, with a thesis on spatial modulation for MIMO-CDMA systems. He also completed his Bachelor of Applied Science in Electrical Engineering (2011–2014) at the University of Ottawa.

Experience

💼 Technical Expertise defines Nordine’s career. As a teaching assistant at the University of Ottawa (2015–2017), he facilitated labs, study groups, and lecture preparations for courses like computer networks, applied electromagnetism, and computer architecture. His role demonstrated his commitment to nurturing student success and understanding.

Research Interests

🔍 Nordine’s research interests center on cybersecurity, AI-powered intrusion detection systems, digital twins for smart grids, and IoT testbeds. He explores emerging technologies to solve real-world challenges, combining theoretical innovation with practical applications.

Awards

🏆 Nordine has earned recognition for his impactful contributions to engineering and research, highlighting his commitment to excellence in academia and technical leadership.

Publications

N. Mchirgui, N. Quadar, et al. The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review. Applied Sciences, 2024. DOI:10.3390/app142310933

N. Quadar, A. Chehri, et al. Intrusion Detection Systems in Automotive Ethernet Networks: Challenges, Opportunities and Future Research Trends. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 2, pp. 62–68.

N. Quadar, M. Rahouti, et al. IoT-AI/Machine Learning Experimental Testbeds: The Missing Piece. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 1, pp. 136–143.

N. Quadar, H. Chaibi, et al. Recommendation Systems: Models, Techniques, Application Fields and Ethical Challenges. In Proceedings of the 7th International Conference on Big Data and Internet of Things (BDIoT ’24), 2024.