Mr. Sangwon Lee | cybersecurity | Best Researcher Award

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Sangwon Lee | cybersecurity | Best Researcher Award

Sangwon Lee, Hoseo University, South Korea

Sangwon Lee is a passionate researcher in the field of cybersecurity πŸ” and artificial intelligence πŸ€–. She received her Bachelor’s degree in Computer Engineering from Hoseo University, South Korea πŸ‡°πŸ‡·, in 2025. Currently, she is pursuing her Master’s in Information Security 🧠 at the same institution. Her research interests focus on AI security, physical security, and hardware-based security threats like clock glitch fault attacks ⏱️⚑. Sangwon is dedicated to advancing secure AI systems by identifying vulnerabilities and developing countermeasures. She is keen on blending academic insights with practical hardware testing to address real-world cybersecurity challenges.

Professional profile :

Orcid

Suitability for Best Researcher Award :

Sangwon Lee demonstrates exceptional promise as a young researcher by combining academic rigor with hands-on practical experimentation. Her deep focus on AI security and hardware-based threats, such as clock glitch fault attacks, highlights her commitment to tackling real-world vulnerabilities in next-generation computing systems. Her research embodies the spirit of innovation, curiosity, and relevance that aligns with the goals of the Best Researcher Award.

Education & Experience :

  • πŸ“˜ B.E. in Computer Engineering, Hoseo University, Republic of Korea (2025)

  • πŸŽ“ M.S. in Information Security (ongoing), Hoseo University

  • πŸ” Researcher in AI & Hardware Security, focusing on fault injection and physical attack resistance

Professional Development :

Sangwon Lee is actively engaged in advanced studies in information security at Hoseo University 🏫. She continuously enhances her skills in cybersecurity 🧩 through hands-on research involving deep neural networks and fault attacks. As part of her academic journey, she explores real-world attack models such as clock glitching and implements robust countermeasures πŸ›‘οΈ. She regularly collaborates with fellow researchers and participates in seminars and workshops to stay updated on the latest developments in AI and hardware security πŸ”¬. Her commitment to learning and innovation positions her as a promising figure in the cybersecurity and AI safety landscape 🌐.

Research Focus Area :

Sangwon Lee’s research is centered around the intersection of AI security πŸ€– and hardware security πŸ› οΈ. Her primary focus involves studying vulnerabilities in deep neural networks exposed to physical fault injection techniques such as clock glitch attacks ⏱️⚑. She investigates how adversaries can exploit hardware-level weaknesses to manipulate AI system behavior and explores effective countermeasures. Her work aims to ensure robustness and trustworthiness in AI applications by integrating secure design principles and fault-resistant architectures πŸ”. This cross-disciplinary approach connects machine learning with embedded system security, contributing significantly to the future of secure intelligent technologies πŸ”„πŸ”.

Awards and Honors :

  • πŸŽ–οΈ Selected for Graduate Research Program in Information Security at Hoseo University

  • πŸ₯‡ Recognized for excellence in undergraduate thesis on AI & Security Integration

  • πŸ“œ Commended for contribution to AI fault attack simulations in academic symposiums

Publication Top Notes :Β 

The publication you’re referring to is titled “Clock Glitch-based Fault Injection Attack on Deep Neural Network”, authored by Hyoju Kang, Seongwoo Hong, Youngju Lee, and Jeacheol Ha from Hoseo University. It was published in 2024 in the Journal of the Korea Institute of Information Security & Cryptology, Volume 34, Issue 5, pages 855–863. The paper investigates the impact of clock glitch-induced fault injections on deep neural networks (DNNs), particularly focusing on the forward propagation process and the softmax activation function. Using the MNIST dataset, the study demonstrates that injecting faults via clock glitches can lead to deterministic misclassifications, depending on system parameters. This research highlights the vulnerability of DNNs to hardware-level fault injections and underscores the need for robust countermeasures.

Citation:

Kang, H., Hong, S., Lee, Y., & Ha, J. (2024). Clock Glitch-based Fault Injection Attack on Deep Neural Network. Journal of the Korea Institute of Information Security & Cryptology, 34(5), 855–863. https://doi.org/10.13089/JKIISC.2024.34.5.855

Conclusion:

Sangwon Lee stands out as a proactive and visionary researcher whose work addresses the pressing security challenges in AI-driven technologies. Her commitment to building resilient, secure systems through both academic inquiry and practical experimentation makes her a highly deserving nominee for the Best Researcher Award.

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

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Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology – Associate Professor at King Faisal University, Saudi Arabia

Dr. Abdulrahman Khalid Alnaim is an accomplished academic and researcher specializing in computer science and information security. With a strong foundation in computer information systems and management information systems, he has dedicated his career to advancing research in emerging technologies such as cybersecurity, cloud computing, and network architecture. His work is characterized by innovative approaches to securing next-generation networks and optimizing system performance, reflecting a commitment to both academic excellence and practical applications in the tech industry.

Profile:

Google Scholar

Education:

Dr. Alnaim earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where he focused on developing secure and efficient computing models. He also holds a Master’s in Management Information Systems from Nova Southeastern University, USA, which enriched his understanding of integrating technology with business strategies. His academic journey began at King Faisal University, Saudi Arabia, where he completed his Bachelor’s degree in Computer Information Systems, laying the groundwork for his passion for research and technology. This diverse educational background has enabled him to approach complex problems with a multidisciplinary perspective.

Experience:

Dr. Alnaim has served at King Faisal University, Saudi Arabia, in various academic roles. Starting as a Teacher Assistant in 2012, he quickly advanced to become a Lecturer and later an Assistant Professor in the Management Information Systems Department within the School of Business. Throughout his tenure, he has contributed significantly to curriculum development, academic research, and student mentorship. His professional journey reflects a consistent commitment to fostering an environment of academic growth, research innovation, and knowledge dissemination.

Research Interests:

Dr. Alnaim’s research interests lie in the domains of cloud technologies, cybersecurity, and network architecture, with a particular focus on emerging trends like 5G/6G networks, network function virtualization (NFV), and edge computing. His work explores the development of robust security frameworks, optimized resource management strategies, and innovative architectures for next-generation networks. His research not only addresses theoretical challenges but also provides practical solutions for enhancing cybersecurity, system efficiency, and data integrity in complex digital environments.

Awards:

While Dr. Alnaim’s distinguished academic career is marked by numerous achievements, his contributions to research have earned him recognition within the academic community. His work has been cited extensively, reflecting its influence on contemporary studies in cybersecurity and network technologies. His dedication to research excellence is evident through his continuous pursuit of knowledge, innovative problem-solving, and commitment to advancing the field of computer science.

Publications πŸ“š:

  1. “Zero Trust Strategies for Cyber-Physical Systems in 6G Networks” (2025) – Mathematics
    This paper discusses advanced security models tailored for cyber-physical systems in 6G environments. πŸš€

  2. “Securing 5G Virtual Networks: A Critical Analysis of SDN, NFV, and Network Slicing Security” (2024) – International Journal of Information Security
    The article provides an in-depth analysis of security vulnerabilities and countermeasures in 5G networks. πŸ”

  3. “Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework” (2024) – Sensors
    This research introduces the CyberGuard framework for enhancing trust management in edge and fog computing environments. 🌐

  4. “Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities” (2024) – Sensors
    A strategic approach to optimizing network slicing for IoT applications in smart cities. πŸ™οΈ

  5. “Classification of Alzheimer’s Disease Using MRI Data Based on Deep Learning Techniques” (2024) – Journal of King Saud University – Computer and Information Sciences
    This study leverages deep learning models to improve the early detection of Alzheimer’s disease using MRI data. 🧠

  6. “Machine-Learning-Based IoT–Edge Computing Healthcare Solutions” (2023) – Electronics
    Focuses on integrating machine learning with IoT and edge computing to enhance healthcare services. πŸ’‘

  7. “A Misuse Pattern for Modifying Non-Control Threats in NFV” (2022) – Future Internet
    Proposes a model to identify and mitigate non-control threats in network function virtualization environments. πŸ–₯️

These publications have collectively garnered significant citations, underscoring their impact on academic research and industry practices. πŸ“ˆ

Conclusion:

Dr. Abdulrahman Khalid Alnaim exemplifies the qualities of an outstanding researcher, with a robust academic background, extensive research contributions, and a commitment to advancing the field of computer science and information security. His work in cybersecurity, cloud technologies, and network architecture has not only enriched academic discourse but also provided practical solutions to real-world challenges.

His innovative approach, combined with a strong publication record and active involvement in academic and research communities, makes him a deserving candidate for the Excellence in Research Award. Dr. Alnaim’s contributions reflect the values of academic rigor, intellectual curiosity, and a relentless pursuit of knowledge that this prestigious award seeks to honor.

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

πŸ† Suitability for Best Researcher AwardΒ 

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.

πŸŽ“ EducationΒ 

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.

πŸ‘©β€πŸ’» 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.

πŸ… 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.

πŸ”¬ Research FocusΒ 

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.

πŸ“–Β Publication Top NotesΒ 

  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

 

 

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

πŸ“Œ Assoc. Prof. Dr. Muharrem Tuncay GenΓ§oğlu is a distinguished researcher in Applied Mathematics, Cryptology, and Cybersecurity. He holds dual PhDsβ€”one in Applied Mathematics from FΔ±rat University (TΓΌrkiye) and another in Cryptology from Vector Sciences Academy (Azerbaijan). With expertise in cybersecurity, cryptographic systems, and artificial intelligence, he has worked with institutions like FΔ±rat 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 TÜBΔ°TAK-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 – FΔ±rat University (2013)
  • Ph.D. in Cryptology – Vector Sciences Academy, Azerbaijan
  • M.Sc. in Applied Mathematics – FΔ±rat University (1995)
  • B.Sc. in Mathematics – FΔ±rat 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 – FΔ±rat 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

πŸ“š Dr. GenΓ§oğlu 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 TÜBΔ°TAK-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

πŸ”¬ Dr. GenΓ§oğlu’s research spans applied mathematics, cybersecurity, cryptology, and artificial intelligence. His TÜBΔ°TAK 1002 project explored random number generation through chemical reactions, a crucial innovation in cryptographic security πŸ”’. His work in blockchain, quantum cryptography, and network security addresses threat modeling, privacy preservation, and cyber intelligence πŸ”. 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

πŸ† Awards & Recognitions:

  • TÜBΔ°TAK 1002 Grant – Project on Random Number Generation using Chemical Reactions πŸ…
  • COST Action Leadership – Contributions to CA18232, CA21109, CA21169 🌍
  • Researcher in Distributed AI Lab – Technical University of Berlin (2014) πŸ€–
  • ISO 27001 Information Security Certification – IRCA-IPC πŸ›‘οΈ
  • Cybersecurity & Cyber-Terrorism Certifications – Various Institutions πŸ”“

Publication Top Notes:

  • πŸ”¬ Use of quantum differential equations in sonic processes – Applied Mathematics and Nonlinear Sciences,Β  (Cited by: 62)
  • πŸ” Importance of Cryptography in Information Security – IOSR Journal of Computer Engineering (IOSR-JCE),Β  (Cited by: 43)
  • 🧠 Numerical simulations to the nonlinear model of interpersonal relationships with time fractional derivative – AIP Conference Proceedings,Β  (Cited by: 43)
  • πŸ”“ Cryptanalysis of a new method of cryptography using Laplace transform hyperbolic functions – Communications in Mathematics and Applications,Β  (Cited by: 24)
  • πŸ”’ Use of integral transform in cryptology – Science and Engineering Journal of FΔ±rat University,Β  (Cited by: 18)
  • 🏫 Ortaokul âğrencilerinin bilgi gΓΌvenliği farkΔ±ndalığı – Savunma Bilimleri Dergisi,Β  (Cited by: 10)

Jinyan Wang | Information Security | Best Researcher Award

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Jinyan Wang | Information Security | Best Researcher Award

Dr. Jinyan Wang, Guangxi Normal University, China.

πŸŽ“Β Dr. Jinyan Wang is a renowned professor at the School of Computer Science and Engineering, Guangxi Normal University, China. With expertise inΒ machine learningΒ andΒ information security, her research addresses critical challenges in data analysis and digital protection.Β πŸ”Β She has authored over 50 impactful publications in prestigious international journals and conferences, contributing significantly to the advancement of computer science.Β πŸ“šΒ Dr. Wang’s academic journey includes advanced degrees in computer science and a visiting scholar position at East China Normal University. 🌏 As an educator and researcher, she is dedicated to fostering innovation and mentoring future technology leaders.Β πŸ’»βœ¨

Publication Profile

Googlescholar

Education & Experience:

  • πŸŽ“Β B.Sc.Β in Computer Science and Information Technology, Northeast Normal University (2005).
  • πŸŽ“Β M.Sc.Β in Computer Science and Information Technology, Northeast Normal University (2008).
  • πŸŽ“Β Ph.D.Β in Computer Science and Information Technology, Northeast Normal University (2011).
  • 🏫 Professor, School of Computer Science and Engineering, Guangxi Normal University, China (Current).
  • 🌏 Visiting Scholar, East China Normal University, China (2019).

 

Suitability for the Award

Professor Jinyan Wang is a highly qualified and accomplished researcher, making her an excellent candidate for the Best Researcher Award. With a solid academic background, including a Ph.D. in Computer Science and Information Technology, she has significantly contributed to the fields of machine learning and information security. Her extensive research output, with over 50 publications in prestigious international journals and conferences, demonstrates her expertise and impact. Her experience as a visiting scholar further enhances her global research perspective. Professor Wang’s dedication to advancing knowledge in her fields of interest positions her as a leading figure in academic research.

Professional Development

🌟 Dr. Jinyan Wang has established herself as a leading figure in computer science, specializing inΒ machine learningΒ andΒ information security. With over 50 research publications in renowned international journals and conferences, she has significantly advanced these fields.Β πŸ“ˆΒ Her academic journey includes earning three degrees from Northeast Normal University and gaining international exposure as a visiting scholar at East China Normal University. Beyond her research, Dr. Wang is dedicated to mentoring the next generation of computer scientists, contributing to both education and innovation in technology.Β πŸŽ“πŸ’»

Research Focus

πŸ”Β Dr. Jinyan Wang’s research centers onΒ machine learningΒ andΒ information security, two critical and evolving areas in computer science. Her work in machine learning explores advanced algorithms to enhance data analysis, predictive modeling, and AI applications.Β πŸ€–Β Simultaneously, her contributions to information security aim to safeguard digital systems and protect sensitive data from cyber threats.Β πŸ”Β With over 50 publications in leading journals and conferences, Dr. Wang is at the forefront of innovative solutions, combining theoretical insights with practical applications to address real-world challenges.Β πŸŒπŸ“Š

Awards and Honors

  • πŸ†Β Best Paper Award – Recognized for excellence in vision-language research.
  • πŸ₯‡Β Graduate Fellowship – National Tsing Hua University, Taiwan.
  • πŸ₯‰Β Outstanding Thesis Award – Shaanxi Normal University, China.
  • πŸŽ–οΈΒ Research Excellence Recognition – vivo AI Lab, 2019.
  • 🌟 Academic Merit Scholarship – Southwest Minzu University, China.

Publication Highlights

  1. A perturb biogeography based optimization with mutation for global numerical optimizationΒ – Cited by 106 (2011)Β πŸ“Š
  2. Two privacy-preserving approaches for publishing transactional data streamsΒ – Cited by 36 (2018)Β πŸ”
  3. Fuzzy multiset finite automata and their languagesΒ – Cited by 34 (2013)Β πŸ”„
  4. Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted imageΒ – Cited by 31 (2019)Β πŸ–ΌοΈ
  5. Two privacy-preserving approaches for data publishing with identity reservationΒ – Cited by 24 (2019)Β πŸ›‘οΈ
  6. Soft polygroupsΒ – Cited by 22 (2011)Β πŸ“
  7. Two approximate algorithms for model countingΒ – Cited by 21 (2017)Β πŸ”’

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

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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

 

 

Prof. Orken Mamyrbayev | Computing Awards | Outstanding Scientist Award

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Prof. Orken Mamyrbayev | Computing Awards | Outstanding Scientist Award

Prof. Orken Mamyrbayev, Institute of Information and Computational Technologies, Kazakhstan

Orken Zhumazhanovich MamyrbayevΒ  in the Almaty region, is an Associate Professor and Ph.D. in Information Systems. He graduated from Abay Kazakh National Pedagogical University in 2001 with a degree in Computer Science. With over 18 years of experience in scientific and pedagogical work, he currently serves as Deputy Director for Science at the Institute of Information and Computational Technologies under the Ministry of Education and Science of Kazakhstan. He is a specialist in speech recognition, digital signal processing, and natural language processing, and has supervised numerous Ph.D. and master’s theses. Mamyrbayev has authored over 100 scientific papers, holds 2 patents, and has completed advanced training in several countries, including Japan, Azerbaijan, and Malaysia. He is an active member of various scientific councils and an academician of the International Academy of Informatization.

Professional Profile:

Orcid

Suitability of Mamyrbayev Orken Zhumazhanovich for the Research for Outstanding Scientist Award

Summary of Suitability:

Mamyrbayev Orken Zhumazhanovich is a highly suitable candidate for the Research for Outstanding Scientist Award due to his extensive contributions to computer science, his leadership in research projects with real-world applications, and his international recognition. His innovative work in speech recognition, natural language processing, and digital signal processing showcases his potential as a leader in scientific advancements. Additionally, his contributions to education and the mentorship of upcoming researchers further strengthen his candidacy for this prestigious award.

πŸŽ“Education:

Orken Zhumazhanovich Mamyrbayev graduated from Abay Kazakh National Pedagogical University in 2001 with a degree in Computer Science and Computerization Management. In 2014, he earned his Ph.D. in Information Systems, successfully defending his dissertation on the topic “Kazakh Speech Recognition Modal System.”

🏒Work Experience:

From 2002 to 2011, Orken Zhumazhanovich Mamyrbayev worked as a Senior Lecturer at the Department of Computer Science and Applied Mathematics at Abay Kazakh National Pedagogical University. From 2012 to 2015, he served as a Researcher at the Laboratory of “Analysis and Modeling of Information Processes.” Since 2015, he has held the position of Deputy Director for Science at the Institute of Information and Computational Technologies under the Ministry of Education and Science of Kazakhstan. Additionally, since 2017, he has been leading the Laboratory of Computer Engineering of Intelligent Systems at the same institute.

πŸ…Awards:

Orken Zhumazhanovich Mamyrbayev has been recognized for his contributions to science and education, receiving the prestigious Certificate of Honor from the Ministry of Education and Science of Kazakhstan. In addition, he has been awarded letters of gratitude from the Institute of Information and Computational Technologies, CS MES RK, for his valuable work and dedication.

Publication Top Notes:

  • A Study of Kazakh Speech Recognition in Hiformer Model
  • An Innovative Technology for Overloading Microshoots in Vitro
  • Enhancing Emoji-Based Sentiment Classification in Urdu Tweets: Fusion Strategies with Multilingual BERT and Emoji Embeddings
  • High Accuracy Microcalcifications Detection of Breast Cancer Using Wiener LTI Tophat Model
  • Infrared Laser Irradiation for Pre-Sowing Seed Treatment: Advancing Germination and Crop Productivity

 

 

 

Prof. Yi-Nan Xu | In-Vehicle Network Security | Best Researcher Award

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Prof. Yi-Nan Xu | In-Vehicle Network Security | Best Researcher Award

Prof. Yi-Nan Xu, College of Engineering/Yanbian University, China

Prof. Yi-Nan Xu is a distinguished professor in the Department of Electronics and Communication Engineering at the College of Engineering, Yanbian University, China πŸ“š. With a profound expertise in automotive electronic control and in-vehicle communication networks, he has made significant contributions to these fields, particularly in system-level chip design and automotive safety 🌟. Professor Xu’s research prowess is evidenced by his authorship of over 50 SCI/EI papers, focusing on fault-tolerant control, communication networks, and intelligent transportation systems πŸ”¬. He has also led prestigious national and provincial projects, advancing fault tolerance mechanisms and security protocols in automotive systems, thus shaping the landscape of automotive technology research and development in China.

🌐 Professional Profile:

Orcid

Scopus

πŸ“š Education and Experience

Yi-Nan Xu is a distinguished professor in the Department of Electronics and Communication Engineering at the College of Engineering, Yanbian University. With a robust background in automotive electronic control and in-vehicle communication networks, he has dedicated his career to advancing these fields. His expertise extends to system-level chip design, contributing significantly to the intersection of technology and automotive safety.

🌟 Academic Achievements

Professor Xu has authored over 50 SCI/EI papers, focusing on fault-tolerant control, communication networks, and intelligent transportation systems. His research has garnered acclaim and has been pivotal in shaping the understanding and development of automotive systems.

πŸ”¬ Research Leadership

He has led multiple prestigious projects, including three national natural science fund projects on fault tolerance mechanisms in automotive systems and security protocols for on-board networks. His contributions also extend to the “Twelfth Five Year Plan” science and technology research project of Jilin Provincial Department of Education, where he focused on the design of on-board communication network systems.

Publication Top Notes:

  • Arduino-based Omnidirectional Mobile Intelligent Vehicle Control System
    • Conference: Proceedings – 2023 3rd International Conference on Robotics, Automation and Intelligent Control, ICRAIC 2023
    • Year: 2023
  • Analysis on Network Security of Intelligent Connected In-vehicle Bus
    • Conference: Proceedings of SPIE – The International Society for Optical Engineering
    • Year: 2023
  • Intelligent Connected Vehicle CAN-FD Bus Network Security Protocol
    • Conference: Proceedings – 2023 International Conference on Mobile Internet, Cloud Computing and Information Security, MICCIS 2023
    • Year: 2023
  • Dynamic Rearrangement Compression Algorithm for Intelligent Connected Vehicles
    • Journal: IEEE Transactions on Vehicular Technology
    • Year: 2022
  • Research of CAN Bus Information Anomaly Detection Based on Convolutional Neural Network
    • Journal: International Journal of Computer Theory and Engineering
    • Year: 2021

 

 

Prof Dr. Jiliang Zhang | Hardware Security | Best Researcher Award

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Prof Dr. Jiliang Zhang | Hardware Security | Best Researcher Award

Prof Dr. Jiliang Zhang, Hunan University, China

Prof. Dr. Jiliang Zhang, an eminent figure in computer science and technology, currently affiliated with Hunan University, China. πŸŽ“ His academic journey includes a Ph.D. in Computer Science and Technology from Hunan University, where he received accolades for his dissertation on “Security and Trust for FPGA-based Systems.” πŸ… Prof. Zhang’s research interests span hardware security, including areas like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs), as well as new computing architectures such as in-memory computing and brain-inspired computing. πŸ”¬ With a rich professional experience, including positions as a research scholar at the University of Maryland and visiting researcher at Tsinghua University, Prof. Zhang brings a wealth of knowledge and expertise to his role as a professor at Hunan University.

Professional Profile:

Scopus

Educational Background πŸŽ“

  • Ph.D. in Computer Science and Technology – Hunan University, China (2015)
    Dissertation: “Security and Trust for FPGA-based Systems” (Outstanding Doctoral Dissertation)
  • B.E. in Chemical Engineering and Technology – Shandong University of Science and Technology, China (2009)

Honors and Awards πŸ…

  • World’s Top 2% Scientists – Stanford University, 2020-2023 (Ranked 36th in 2023 and 16th in 2022 in computer hardware and architecture)
  • CCF Distinguished Lecturer – 2022, 2023
  • Second Natural Science Award – Hunan Province, 2022

Research Interests πŸ”¬

  • Hardware Security: Physical Unclonable Functions (PUFs), True Random Number Generators (TRNGs), Hardware Obfuscation, IP Protection, FPGA Security, Hardware Trojan Detection, Cryptographic Accelerators, CPU Security, and Applications in Secure Systems.
  • New Computing Architectures: In-memory Computing and Brain-inspired Computing.

Professional Experience 🏫

  • Professor – Hunan University (Dec 2020 – Present)
  • Associate Professor – Hunan University (May 2017 – Dec 2020)
  • Associate Professor – Northeastern University (May 2015 – Apr 2017)
  • Research Scholar – University of Maryland, College Park (Sept 2013 – Sept 2014)
  • Visiting Researcher – Tsinghua University, Beijing (Aug 2012 – Sept 2012; Sept 2010 – Jun 2011)

Google Scholar Metrics πŸ“Š

  • Citations: 3025
  • H-index: 29

Publication Top Notes:

  1. Design and Application of Programmable Analog Circuit for Solving Lyapunov Matrix Equation Based on Memristors
    • Journal: IEEE Transactions on Industrial Electronics
    • Year: 2024
  1. Design of Artificial Neurons of Memristive Neuromorphic Networks Based on Biological Neural Dynamics and Structures
    • Journal: IEEE Transactions on Circuits and Systems I: Regular Papers
    • Year: 2024
  2. FTOP: An Efficient Flow Table Overflow Preventing System for Switches in SDN
    • Journal: IEEE Transactions on Network Science and Engineering
    • Year: 2024
  3. Quantization Backdoors to Deep Learning Commercial Frameworks
    • Journal: IEEE Transactions on Dependable and Secure Computing
    • Year: 2024
  4. Timing Side-channel Attacks and Countermeasures in CPU Microarchitectures
    • Journal: ACM Computing Surveys
    • Year: 2024

 

 

 

 

 

Dr. Negalign Wake Hundera | Network Security and Cryptography | Best Researcher Award

Published on by Network Awards

Dr. Negalign Wake Hundera | Network Security and Cryptography | Best Researcher Award

Dr. Negalign Wake Hundera, Zhejiang Normal University, China

Dr. Negalign Wake Hundera is an accomplished academician and researcher with expertise in network security, cryptography, and cloud computing. Holding a Ph.D. in Software Engineering from the University of Electronic Science and Technology of China, and prior degrees from esteemed institutions in both China and Ethiopia, he has a strong foundation in academia. Currently serving as a Postdoctoral Research Fellow at Zhejiang Normal University, his contributions extend beyond research to mentoring students and securing funding for projects. With a passion for exploring the intersection of technology and real-world applications, he seeks to leverage his skills in innovative environments. Outside academia, he enjoys reading, cooking, and sports like football and table tennis. πŸŒπŸ”’πŸ–₯️

Professional Profile:

Google Scholar

Orcid

πŸŽ“ Education:

Negalign holds a Ph.D. in Software Engineering from the University of Electronic Science and Technology of China, along with an M.Sc. in Computer Science and Technology from the same institution. He earned his Bachelor’s degree in Information Technology from Jimma University, Ethiopia. His research interests span various areas including network security, public key cryptography, IoT, cloud computing, and deep learning.

πŸ’Ό Employment History:

Currently serving as a Postdoctoral Research Fellow at Zhejiang Normal University, Negalign has been actively engaged in research and academic activities. Prior to this, he worked as an Assistance Professor for Computer Science at Wolkite University, Ethiopia, and as a Lecturer for Computer Science Department at the same university. He also served as an Information Communication and Network Infrastructure Team Leader at Wolkite University.

πŸ”§ Skills:

Negalign possesses expertise in academic writing, teaching, programming languages such as Python, C, and Java, network administration and designing, LANs/WANs, and Internet/Intranet management. He is proficient in troubleshooting network connectivity issues and is well-versed in various protocols and security measures.

πŸ“š Publications:

Negalign has numerous publications in esteemed journals and conferences, covering topics like network security, cloud computing, IoT, and cryptography. His research contributions have been recognized in various academic circles.

πŸ† Awards & Certifications:

He has received several academic achievement certificates and awards from the University of Electronic Science and Technology of China. Additionally, he holds certifications in Cisco instruction, maintenance and networking training, and SPSS.

Publication Top Notes:

  1. Title: Permission-based separation of duty in dynamic role-based access control model
    • Journal: Symmetry
    • Year: 2019
    • Citations: 24
  2. Title: A Secure and Efficient Identity-Based Proxy Signcryption in Cloud Data Sharing
    • Journal: KSII Transactions on Internet and Information Systems (TIIS)
    • Year: 2020
    • Citations: 18
  3. Title: A hybrid cnn-lstm model for virtual machine workload forecasting in cloud data center
    • Conference: 2021 18th International Computer Conference on Wavelet Active Media
    • Year: 2021
    • Citations: 11
  4. Title: The Internet of vehicles and smart cities
    • Journal: Annals of Telecommunications
    • Year: 2021
    • Citations: 10
  5. Title: DNACDS: Cloud IoE big data security and accessing scheme based on DNA cryptography
    • Journal: Frontiers of Computer Science
    • Year: 2024