Veneta Aleksieva | Blockchain | Best Researcher Award

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Prof. Dr. Veneta Aleksieva | Blockchain | Best Researcher Award 

Prof. Dr. Veneta Aleksieva | Technical University of Varna | Bulgaria

Prof. Dr. Veneta Aleksieva is a distinguished researcher and academic at the Technical University of Varna, Bulgaria, specializing in computer networks, network security, and wireless communication technologies. With a Scopus h-index of 8, 61 publications, and over 233 citations, she has made significant contributions to network modeling, simulation, and optimization—particularly in MPLS, LTE, and hybrid wireless networks. Her research extends to e-learning systems, quality of service (QoS) enhancement, intelligent traffic scheduling, and blockchain-based smart contracts. She has developed simulation frameworks for improving the efficiency and reliability of network infrastructures and has published extensively in international journals and conferences. As a Cisco Certified Network Associate (CCNA) and Instructor, she integrates academic rigor with practical training in network design and administration. Prof. Dr. Veneta Aleksieva ’s work bridges education, applied engineering, and emerging technologies, promoting innovation in both teaching and research within the field of computer science and network engineering.

Profiles: Scopus | Google Scholar

Featured Publication 

Aleksieva, V., & Nenov, H. (2005). Quality of feedback based on electronic tests in e-learning education. Computer Science and Technologies, (2), 81–87. ISSN 1312-3335.

Nenov, H., & Aleksieva, V. (2006). Quality of feedback in e-learning education. In Second National Conference on E-Learning in Higher Education (pp. 129–132). University Publishing House “St. Kliment Ohridski”. ISBN-10: 954-07-2413-9; ISBN-13: 978-954-07-2413-3.

Nenov, H., & Aleksieva, V. (2006). Formation of assessment based on electronic tests. In Second National Conference on E-Learning in Higher Education (pp. 129–132). University Publishing House “St. Kliment Ohridski”. ISBN-10: 954-07-2413-9; ISBN-13: 978-954-07-2413-3.

Aleksieva, V. (2007). The problems in distance learning. In iCEST 2007: Proceedings of Papers (Vol. 2, pp. 621–622). Bitola. ISBN 9989-786-06-2.

Aleksieva, V., & Antonov, P. (2008). A model for network performance analysis in case of transfer of large image files. In ICEST 2008, Nish, Serbia, July 28–31, 2008 (pp. 60–67). ISBN 978-86-85195-59-4.

Dr. Shuhao Shen | Cybersecurity | Best Researcher Award

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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 : 

Title:  BinCoFer: 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.

Ms. Ujunwa Madububa Mbachu | Cybersecurity | Best Researcher Award

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Ms. Ujunwa Madububa Mbachu | Cybersecurity | Best Researcher Award

Ms. Ujunwa Madububa Mbachu, University of Southern Mississippi, United States

Ms. Ujunwa Madububa Mbachu is a Ph.D. candidate in Computer Science (Cybersecurity) at the University of Southern Mississippi, USA. She is a Visiting Instructor at the School of Computing Sciences and Computer Engineering and a Research Associate at the SPEN Lab, focusing on security and privacy in emerging networks. With extensive experience in teaching, research, and industry leadership, she is the President of the Cyberwatch Foundation, promoting inclusivity in cybersecurity education. Her expertise spans cybersecurity, machine learning, cloud computing, and privacy protection. She has received prestigious awards, including the Dissertation Completion Grant and Hall of Fame Induction at her university.

🌍 Professional Profile:

Google Scholar

🏆 Suitability for Best Researcher Award 

Ms. Mbachu is an exceptional candidate for the Best Researcher Award due to her groundbreaking contributions in cybersecurity, privacy, and emerging network security. Her Ph.D. research on Secure and Privacy-Aware Traffic Management Services in Autonomous Vehicles addresses critical global challenges in data protection and smart transportation. She has authored impactful research, led cybersecurity initiatives, and mentored students in computing sciences. As a leader in the Cyberwatch Foundation, she actively bridges academic research and real-world applications. Her dedication to advancing cybersecurity knowledge and fostering technological inclusivity makes her a highly deserving nominee for this prestigious recognition.

🎓 Education 

Ms. Mbachu is currently pursuing a Ph.D. in Computer Science (Cybersecurity) at the University of Southern Mississippi (2021–2025), with a dissertation on Secure and Privacy-Aware Traffic Management Services in Autonomous Vehicles, under the supervision of Dr. Ahmed Sherif. She earned an M.Sc. in Information Technology from the National Open University (NOUN), Nigeria (2017), focusing on the socioeconomic implications of national security and privacy systems. Her academic foundation includes a strong background in computer science, cybersecurity, and privacy research, preparing her for innovative contributions in data security, artificial intelligence, and cloud computing.

👩‍💻 Professional Experience

Ms. Mbachu is a Visiting Instructor at the University of Southern Mississippi, teaching computer science and IT courses across various modalities. She has also served as a Graduate Teaching Assistant, mentoring students and supporting research in cybersecurity. As a Research Associate at the SPEN Lab, she actively investigates security and privacy challenges in emerging networks. In the industry, she is the President of Cyberwatch Foundation, driving cybersecurity education initiatives. Her roles in academia and leadership demonstrate her commitment to advancing cybersecurity knowledge and empowering future researchers in the field.

🏅 Awards & Honors

Ms. Mbachu has received numerous accolades, including the 2025 Graduate School Dissertation Completion Grant and Hall of Fame Induction at the University of Southern Mississippi. She was also awarded the 2025 Student Travel Grant for her outstanding contributions to research. In 2021, she was honored with the College of Arts & Science Student Travel Award for her impactful academic work. These recognitions highlight her excellence in cybersecurity research, academic performance, and leadership in technology education. Her commitment to innovation and mentorship in cybersecurity has earned her prestigious acknowledgments from both academic and professional institutions.

🔬 Research Focus 

Ms. Mbachu’s research spans cybersecurity, privacy protection, machine learning, deep learning, and cloud computing. Her work focuses on securing emerging networks, with particular interest in privacy-aware traffic management in autonomous vehicles. She explores how artificial intelligence and cryptographic models enhance data security in smart infrastructures. Her studies also address cloud security, cyber-attack prevention, and AI-driven risk assessments. Through her leadership at the Cyberwatch Foundation, she advocates for inclusive cybersecurity education. Her multidisciplinary research contributes to both theoretical advancements and real-world cybersecurity applications, ensuring safer digital ecosystems in emerging technologies.

📖 Publication Top Notes 

  1. Machine Learning Techniques to Predict Mental Health Diagnoses: A Systematic Literature Review
    • Year: 2024
    • Citations: 7
  2. Predictive Machine Learning Approaches for Mental Health Diagnoses in College Students
    • Year: 2024
  3. A Review of Machine Learning Techniques to Predict Mental Health Diagnoses
    • Year: 2024
  1. Secure and Privacy-Preserving Aggregation Scheme for Traffic Management Systems
    • Year: 2023
    • Citations: 2
  2. Hardware-Acceleration Based Privacy-Aware Authentication Scheme for Internet of Vehicles
    • Year: 2024
  3. Privacy-Aware and Hardware Acceleration-Based Aggregation Scheme for Smart Grid Networks
    • Year: 2023

 

 

Dr. Obada Al-Khatib | Network Security | Best Researcher Award

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Dr. Obada Al-Khatib | Network Security | Best Researcher Award

Dr. Obada Al-Khatib, University of Wollongong in Dubai, United Arab Emirates

Dr. Obada Al-Khatib is an esteemed researcher and academic specializing in electrical and information engineering. He currently serves as an Assistant Professor and Discipline Leader for Electrical, Computer, and Telecommunications Engineering at the University of Wollongong Dubai. Holding a Ph.D. from The University of Sydney, he has made significant contributions to wireless networks, IoT applications, and AI-driven signal processing. With industry experience as an electrical engineer and memberships in IEEE and Engineers Australia, Dr. Al-Khatib bridges the gap between academia and industry. His dedication to research, mentorship, and technological advancements makes him a prominent figure in engineering education. ⚡📡

🌍 Professional Profile:

Google Scholar

🏆 Suitability for Award

Dr. Obada Al-Khatib’s exceptional contributions to wireless networks, IoT applications, and AI-driven signal processing position him as an outstanding candidate for the Best Researcher Award. His research significantly enhances the optimization and security of modern communication networks, addressing global technological challenges. His leadership as Discipline Leader at the University of Wollongong Dubai demonstrates his commitment to education and innovation. With numerous publications, industry experience, and professional memberships, Dr. Al-Khatib’s work has broad academic and industrial impact. Recognizing his achievements would highlight his role in advancing cutting-edge research in electrical and information engineering. 🏆📶

🎓 Education 

Dr. Obada Al-Khatib holds a Ph.D. in Electrical and Information Engineering from The University of Sydney, Australia (2015), where he focused on optimizing wireless networks and communication systems. He further pursued a Master of Education in Higher Education from the University of Wollongong, Australia (2017), enhancing his expertise in academic leadership and pedagogy. Additionally, he earned a Master of Engineering in Communication and Computer from the National University of Malaysia (2010), where he explored advanced networking technologies. His diverse educational background equips him with a unique combination of technical expertise and teaching excellence. 🎓📡

🔬 Experience 

Dr. Al-Khatib has extensive experience in both academia and industry. Since 2016, he has been an Assistant Professor at the University of Wollongong Dubai, where he also serves as Discipline Leader for Electrical, Computer, and Telecommunications Engineering (since 2022). His industry background includes working as an Electrical Engineer at CCIC in Qatar (2006-2009), gaining hands-on experience in large-scale engineering projects. He has also contributed to educational development by mentoring students and serving on university committees, shaping academic policies. His expertise in wireless networks, AI applications, and network security makes him a leader in the field. ⚡🔧

🏅 Awards and Honors 

Dr. Obada Al-Khatib has received numerous accolades for his contributions to research and academia. His work on wireless networks optimization and AI-driven signal processing has been recognized in IEEE conferences and journals. As an active IEEE member, he has contributed to high-impact publications and technical committees. His role as Discipline Leader at the University of Wollongong Dubai reflects his leadership and dedication to academic excellence. Additionally, his achievements in higher education development and mentoring have earned him recognition within the university. His expertise and contributions continue to influence the evolution of communication engineering. 🏅📡

📶 Research Focus 

Dr. Al-Khatib’s research spans wireless networks optimization, IoT applications, AI-driven signal processing, machine learning, mobile edge computing, and network security. His work focuses on enhancing network performance, ensuring secure communications, and leveraging AI for smarter signal processing. His studies in 5G/6G networks, cloud computing, and energy-efficient communications contribute to next-generation network advancements. Additionally, his research on IoT security and edge computing addresses challenges in data privacy and system resilience. By integrating AI and machine learning into wireless networks, Dr. Al-Khatib pioneers innovations that drive the future of smart connectivity. 🌍📶

📖 Publication Top Notes 

  • Traffic Modeling and Optimization in Public and Private Wireless Access Networks for Smart Grids
    • Year: 2014
    • Citations: 30
  • Traffic Modeling for Machine-to-Machine (M2M) Last Mile Wireless Access Networks
    • Year: 2014
    • Citations: 29
  • Spectrum Sharing in Multi-Tenant 5G Cellular Networks: Modeling and Planning
    • Year: 2018
    • Citations: 26
  • Queuing Analysis for Smart Grid Communications in Wireless Access Networks
    • Year: 2014
    • Citations: 10
  • Pursuit Learning-Based Joint Pilot Allocation and Multi-Base Station Association in a Distributed Massive MIMO Network
    • Year: 2020
    • Citations: 8

 

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Cybersecurity | Best Researcher Award

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Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Cybersecurity | Best Researcher Award

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu | Fırat University | Turkey

📌 Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu is a distinguished researcher in Applied Mathematics, Cryptology, and Cybersecurity. He holds dual PhDs—one in Applied Mathematics from Fırat University (Türkiye) and another in Cryptology from Vector Sciences Academy (Azerbaijan). With expertise in cybersecurity, cryptographic systems, and artificial intelligence, he has worked with institutions like Fırat University, National Defense University, and Ahmet Yesevi University. His research spans random number generation, blockchain, and quantum computing, and he has published extensively in international journals. A member of multiple prestigious associations, he is actively involved in COST projects and TÜBİTAK-funded research.

Professional Profile:

Google Scholar

Suitability for Best Researcher Award

Assoc. Prof. Dr. Muharrem Tuncay Gençoğlu is a highly deserving candidate for the Best Researcher Award due to his groundbreaking contributions to Applied Mathematics, Cryptology, and Cybersecurity. His dual PhDs and extensive work with academic and defense institutions highlight his expertise and leadership in these critical fields.

Education & Experience

  • Ph.D. in Applied Mathematics – Fırat University (2013)
  • Ph.D. in Cryptology – Vector Sciences Academy, Azerbaijan
  • M.Sc. in Applied Mathematics – Fırat University (1995)
  • B.Sc. in Mathematics – Fırat University (1992)
  • B.Sc. in Mathematical Engineering – Istanbul Technical University (1997)
  • B.Sc. in Computer Engineering – Texas A&M University (2017)
  • International Relations (English, Ongoing) – Anadolu University
  • Senior Associate Professor – Fırat University (2015-Present)
  • Lecturer & Researcher – National Defense University (2017-Present)
  • Lecturer – Ahmet Yesevi University
  • Postdoctoral Researcher – Technical University of Berlin (2014)
  • Head of Department & Teacher – Private Sector (1988-2004)
  • Chairman of the Board – TEB Eğitim Hizmetleri (2004-2010)

Professional Development

📚 Dr. Gençoğlu has actively contributed to cybersecurity, cryptographic modeling, and artificial intelligence. He has received specialized training in ISO 27001 Information Security, Cyber-Terrorism, and Cyber Defense. As an academic advisor, he has guided over 50 master’s theses, including current research on cryptocurrency analysis using deep learning. He has led major TÜBİTAK-funded projects and is a member of international research groups like COST Actions. His collaborations with global cybersecurity organizations showcase his dedication to strengthening data security and cryptographic resilience.

Research Focus

🔬 Dr. Gençoğlu’s research spans applied mathematics, cybersecurity, cryptology, and artificial intelligence. His TÜBİTAK 1002 project explored random number generation through chemical reactions, a crucial innovation in cryptographic security 🔢. His work in blockchain, quantum cryptography, and network security addresses threat modeling, privacy preservation, and cyber intelligence 🔐. As a principal investigator in CHIST-ERA Distributed Systems, he contributes to privacy-enhancing cryptographic techniques. His contributions in COST Actions on mathematical modeling, quantum networks, and biological computation further cement his role as a leader in future-proof cryptographic systems.

Awards & Honors

🏆 Awards & Recognitions:

  • TÜBİTAK 1002 Grant – Project on Random Number Generation using Chemical Reactions 🏅
  • COST Action Leadership – Contributions to CA18232, CA21109, CA21169 🌍
  • Researcher in Distributed AI Lab – Technical University of Berlin (2014) 🤖
  • ISO 27001 Information Security Certification – IRCA-IPC 🛡️
  • Cybersecurity & Cyber-Terrorism Certifications – Various Institutions 🔓

Publication Top Notes:

  • 🔬 Use of quantum differential equations in sonic processes – Applied Mathematics and Nonlinear Sciences,  (Cited by: 62)
  • 🔐 Importance of Cryptography in Information Security – IOSR Journal of Computer Engineering (IOSR-JCE),  (Cited by: 43)
  • 🧠 Numerical simulations to the nonlinear model of interpersonal relationships with time fractional derivative – AIP Conference Proceedings,  (Cited by: 43)
  • 🔓 Cryptanalysis of a new method of cryptography using Laplace transform hyperbolic functions – Communications in Mathematics and Applications,  (Cited by: 24)
  • 🔢 Use of integral transform in cryptology – Science and Engineering Journal of Fırat University,  (Cited by: 18)
  • 🏫 Ortaokul öğrencilerinin bilgi güvenliği farkındalığı – Savunma Bilimleri Dergisi,  (Cited by: 10)

Dr. Xinjiao Li | Blockchain Privacy | Best Researcher Award

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Dr. Xinjiao Li | Blockchain Privacy | Best Researcher Award

Dr. Xinjiao Li, Dalian University of Technology, China

Dr. Xinjiao Li is a distinguished scholar in Software Engineering at Dalian University of Technology, China, where she earned both her Ph.D. and Master’s degrees. Specializing in high-performance computing and parallel and distributed systems, Dr. Li has made significant contributions as a Program Committee Member for prominent IEEE conferences, including IEEE ICPADS 2023 and IEEE HPCC conferences in 2020 and 2022. Her academic and professional journey reflects a deep commitment to advancing research and innovation in computing technologies.

Professional Profile:

Scopus

🎓 Education:

Dr. Xinjiao Li earned a Ph.D. in Software Engineering from Dalian University of Technology in 2024, following a Master’s degree in the same field from the same institution in 2016. Li’s academic journey at Dalian University has been marked by a strong focus on advanced software engineering principles, equipping him with extensive expertise and research capabilities in this domain.

💼 Work Experience:

Dr. Xinjiao Li has extensive experience in high-performance computing and parallel and distributed systems, demonstrated through her roles as a Program Committee Member for several prestigious IEEE conferences. She contributed to the IEEE ICPADS 2023 in Hainan and the IEEE HPCC conferences in Chengdu in 2022 and 2020, where she provided remote service to advance research and innovation in these fields. Dr. Li’s expertise and involvement in these conferences highlight her commitment to fostering the development of cutting-edge technologies in computing.

Publication Top Notes:

  • Title: Utility-aware Privacy Perturbation for Training Data
    • Year: 2024
  • Title: Progress and Future Challenges of Security Attacks and Defense Mechanisms in Machine Learning
    • Year: 2021
    • Citations: 9
  • Title: Probabilistic response-time analysis for real-time systems in body area sensor networks
    • Year: 2015
    • Citations: 6