Mr. Yixiang Zhang | Cybersecurity | Best Researcher Award

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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.

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 🔐 and artificial intelligence 🤖. She received her Bachelor’s degree in Computer Engineering from Hoseo University, South Korea 🇰🇷, 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 :

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

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

  • 🔍 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 🛡️. She regularly collaborates with fellow researchers and participates in seminars and workshops to stay updated on the latest developments in AI and hardware security 🔬. 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 🤖 and hardware security 🛠️. 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 🔐. This cross-disciplinary approach connects machine learning with embedded system security, contributing significantly to the future of secure intelligent technologies 🔄🔍.

Awards and Honors :

  • 🎖️ Selected for Graduate Research Program in Information Security at Hoseo University

  • 🥇 Recognized for excellence in undergraduate thesis on AI & Security Integration

  • 📜 Commended for contribution to AI fault attack simulations in academic symposiums

Publication Top Notes : 

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.

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.

🎓 Dr. Jinyan Wang is a renowned professor at the School of Computer Science and Engineering, Guangxi Normal University, China. With expertise in machine learning and information security, her research addresses critical challenges in data analysis and digital protection. 🔍 She has authored over 50 impactful publications in prestigious international journals and conferences, contributing significantly to the advancement of computer science. 📚 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. 💻✨

Publication Profile

Googlescholar

Education & Experience:

  • 🎓 B.Sc. in Computer Science and Information Technology, Northeast Normal University (2005).
  • 🎓 M.Sc. in Computer Science and Information Technology, Northeast Normal University (2008).
  • 🎓 Ph.D. 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 in machine learning and information security. With over 50 research publications in renowned international journals and conferences, she has significantly advanced these fields. 📈 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. 🎓💻

Research Focus

🔍 Dr. Jinyan Wang’s research centers on machine learning and 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. 🤖 Simultaneously, her contributions to information security aim to safeguard digital systems and protect sensitive data from cyber threats. 🔐 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. 🌐📊

Awards and Honors

  • 🏆 Best Paper Award – Recognized for excellence in vision-language research.
  • 🥇 Graduate Fellowship – National Tsing Hua University, Taiwan.
  • 🥉 Outstanding Thesis Award – Shaanxi Normal University, China.
  • 🎖️ 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 optimization – Cited by 106 (2011) 📊
  2. Two privacy-preserving approaches for publishing transactional data streams – Cited by 36 (2018) 🔐
  3. Fuzzy multiset finite automata and their languages – Cited by 34 (2013) 🔄
  4. Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image – Cited by 31 (2019) 🖼️
  5. Two privacy-preserving approaches for data publishing with identity reservation – Cited by 24 (2019) 🛡️
  6. Soft polygroups – Cited by 22 (2011) 📐
  7. Two approximate algorithms for model counting – Cited by 21 (2017) 🔢

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

 

 

Ms. Qiping Wei | Security Analysis | Women Researcher Award

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Ms. Qiping Wei | Security Analysis | Women Researcher Award

Ms. Qiping Wei, University of Texas at Arlington, United States

Ms. Wei, a Ph.D. graduate in Computer Science with a focus on testing and security analysis of Solidity smart contracts, has demonstrated remarkable dedication to advancing blockchain technology. Her perseverance, highlighted by the extensive revision process of her first journal paper published in 2024, underscores her commitment to high-quality research. Leading innovative projects that integrate reinforcement learning and large language models to enhance Solidity smart contract security, Ms. Wei is at the forefront of blockchain technology and AI applications. Her impactful work and leadership in the field reflect her significant contributions and align with the values of the Research for Women Researcher Award.

Professional Profile:

Orcid
Google Scholar

Suitability for the Award

Ms. Qiping Wei is a highly suitable candidate for the Research for Women Researcher Award. Her specialization in the testing and security analysis of Solidity smart contracts is timely and critical, given the growing importance of blockchain technology. Her successful publication record, leadership in innovative research projects, and contributions to global technology make her a standout researcher in her field.

Academic Background and Achievements:

Ms. Wei has an impressive academic trajectory, having completed her Ph.D. in Computer Science with a specialization in testing and security analysis of Solidity smart contracts. Her educational journey, marked by persistence and dedication, reflects her commitment to advancing in a challenging field.

Her determination is evident from the multiple rounds of revision her first paper underwent before its eventual acceptance, highlighting her resilience and dedication to high-quality research. This perseverance culminated in the publication of her first journal paper in 2024, showcasing her contributions to the field.

Research Contributions:

Ms. Wei’s research focuses on the critical area of blockchain technology, specifically the testing and security analysis of Solidity smart contracts. This work is increasingly important as blockchain systems become more integral to global networks.

She is leading two innovative projects that utilize reinforcement learning and large language models (LLMs) to improve the symbolic execution of Solidity smart contracts. These projects aim to enhance the security and reliability of blockchain systems, demonstrating her leadership in advancing technology at the intersection of AI and blockchain.

Impact and Innovation:

Her work has made a tangible impact, as evidenced by the significant interest in her publications. Her paper on the application of LLMs in engineering has garnered substantial attention, indicating the relevance and significance of her research.

By addressing security challenges in blockchain technology and exploring advanced AI techniques, Ms. Wei is pushing the boundaries of how these technologies can be applied to improve digital infrastructure. This aligns with the values of the Research for Women Researcher Award, which celebrates innovation and excellence in technology.

Professional Experience and Leadership:

Ms. Wei’s involvement in part-time academic roles during her undergraduate years and her subsequent research efforts reflect her deep commitment to the field. Her leadership in managing research projects and contributing to advancements in blockchain security further underscores her suitability for this award.

Publication Top Note:

  • Title: Mining New Scientific Research Ideas from Quantum Computers and Quantum Communications
    • Year: 2019
    • Cited by: 6
  • Title: SmartExecutor: Coverage-Driven Symbolic Execution Guided by a Function Dependency Graph
    • Year: 2023
    • Cited by: 2
  • Title: MagicMirror: Towards High-Coverage Fuzzing of Smart Contracts
    • Year: 2023
  • Title: Sligpt: A Large Language Model-Based Approach for Data Dependency Analysis on Solidity Smart Contracts
    • Year: 2024
  • Title: SmartExecutor: Coverage-Driven Symbolic Execution Guided via State Prioritization and Function Selection
    • Year: 2024

 

 

Dr. Samah Alhazmi | Security Awards | Best Researcher Award

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Dr. Samah Alhazmi | Security Awards | Best Researcher Award

Dr. Samah Alhazmi, Saudi Electronic University, Saudi Arabia

Dr. Samah Alhazmi, an Associate Professor at Saudi Electronic University (SEU), holds a Ph.D. in Computer Science from the University of Manchester, UK, with a focus on AI, Machine Learning, and NLP. She also earned an M.Sc. in Advanced Computer Science from the same institution and a B.Sc. from King Abdul Aziz University, Jeddah. Dr. Alhazmi has served as Assistant Professor, Lecturer, and held leadership roles including Vice-Dean for Academic Affairs and Head of the Computer Science Department at SEU. Her expertise spans Data Collection and Analysis, Business and Policy Analysis, Project Management, and Curriculum Planning. She has received prestigious awards such as the IBM Blockchain Developer – Explorer Award and the Predictive Analytics Modeler – Explorer and Mastery Awards. Her notable publications include works on blockchain applications in education, Arabic SentiWordNet, and energy management in wireless sensor networks.

🌍 Professional Profile:

Google Scholar

Suitability for the Best Researcher Award

  1. Research Excellence: Dr. Alhazmi’s research contributions in artificial intelligence, data mining, and sentiment analysis have made a significant impact in her field. Her work on blockchain applications and sentiment analysis is widely cited, demonstrating its influence and relevance.
  2. Leadership and Service: Dr. Alhazmi has held several leadership positions at SEU, including Vice-Dean for Academic Affairs and Head of the Computer Science Department. Her leadership has been pivotal in curriculum development, academic policy enhancement, and strategic planning.
  3. Awards and Recognition: The numerous awards she has received highlight her exceptional achievements and contributions to research and professional development. Her awards in blockchain development and predictive analytics reflect her proficiency in cutting-edge technologies.
  4. Teaching and Mentorship: Dr. Alhazmi has been actively involved in teaching and mentoring students, guiding their academic and professional growth. Her role in designing innovative curricula and supervising research projects underscores her commitment to education.
  5. Administrative and Strategic Contributions: Her involvement in committees related to scheduling, policy implementation, and accreditation demonstrates her effectiveness in academic administration and strategic planning.

🎓 Education:

Dr. Samah Alhazmi earned her Ph.D. in Computer Science from the University of Manchester, UK, focusing on AI, Machine Learning, and NLP. She also holds an M.Sc. in Advanced Computer Science from the same institution and a B.Sc. in Computer Science from King Abdul Aziz University, Jeddah.

🏛️ Professional Experience:

She is currently an Associate Professor at Saudi Electronic University (SEU), where she has also served as Assistant Professor and Lecturer. Dr. Alhazmi has held key roles including Vice-Dean for Academic Affairs, Head of the Computer Science Department, and various leadership positions within SEU.

🔍 Key Skills:

Her expertise includes Data Collection and Analysis, Business and Policy Analysis, Project Management, and Curriculum Planning. She is recognized for her leadership and research development skills.

🏆 Awards and Honors:

Dr. Alhazmi has received multiple awards, including the IBM Blockchain Developer – Explorer Award and Predictive Analytics Modeler – Explorer and Mastery Awards. She was also honored with distinction for her M.Sc. dissertation and has received several publication awards.

📚 Research Contributions:

Notable publications include “Blockchain-based Applications in Education” (Applied Sciences, 2019), “Arabic SentiWordNet in Relation to SentiWordNet 3.0” (Linguistic Research, 2013), and “Efficient Clustering Based Routing for Energy Management in Wireless Sensor Networks” (Electronics, 2022).

Publication Top Notes:

  • Title: Blockchain-Based Applications in Education: A Systematic Review
    • Year: 2019
    • Citations: 468
  • Title: Arabic SentiWordNet in Relation to SentiWordNet 3.0
    • Year: 2013
    • Citations: 23
  • Title: Efficient Clustering Based Routing for Energy Management in Wireless Sensor Network-Assisted Internet of Things
    • Year: 2022
    • Citations: 11
  • Title: Detection of Primary User Emulation Attack Using the Differential Evolution Algorithm in Cognitive Radio Networks
    • Year: 2022
    • Citations: 10
  • Title: Applsci-09-02400. Pdf
    • Year: 2019
    • Citations: 5

 

 

 

Prof. Daehee Jang | Software Security Awards | Best Researcher Award

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Prof. Daehee Jang | Software Security Awards | Best Researcher Award

Prof. Daehee Jang, Kyung Hee University, South Korea

Prof. Daehee Jang is an accomplished academic currently serving as Assistant Professor at Kyunghee University’s Computer Engineering Department in South Korea. He holds a Ph.D. and M.S. in Information Security from the Korea Advanced Institute of Science and Technology (KAIST), where he studied under Prof. Brent Byunghoon Kang, and a B.S. in Computer Engineering from Hanyang University. Dr. Jang’s professional journey includes roles as a Postdoctoral Researcher at Georgia Tech and Assistant Professor at Sungshin Women’s University. He has received prestigious honors such as the Grand Prize in the Information Security Paper Competition and the NAVER Ph.D. Fellowship Award, showcasing his significant contributions to the field of information security.

Professional Profile:

Google Scholar

🎓 Educational Background:

Dr. Daehee Jang earned his Ph.D. and M.S. degrees from the Korea Advanced Institute of Science and Technology (KAIST), specializing in Information Security under the guidance of Prof. Brent Byunghoon Kang. He also holds a B.S. in Computer Engineering from Hanyang University, graduating with honors after completing military service.

💼 Professional Journey:

Currently serving as Assistant Professor at Kyunghee University in the Computer Engineering Department, Dr. Jang previously held a similar role at Sungshin Women’s University. He also gained international research experience as a Postdoctoral Researcher at Georgia Tech under the mentorship of Prof. Taesoo Kim.

🏆 Academic Achievements:

Dr. Jang has received numerous accolades, including the Grand Prize in the 2017 Information Security Paper Competition and the Excellence Award in multiple editions of the Korea Information Security Paper Competition. His contributions to the field have been recognized with awards such as the NAVER Ph.D. Fellowship Award in 2016.

Publication Top Notes:

 

 

Prof. syed Hasan | Cloud Security | Best Scholar Award

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Prof. syed Hasan | Cloud Security | Best Scholar Award

Prof. syed Hasan, King Abdulaziz Unversity, Saudi Arabia

Prof. Syed Hasan is a distinguished academic and researcher currently serving as a Professor at King Abdulaziz University, Saudi Arabia. He holds a Ph.D. in Computer Science from Jamia Delhi, complemented by an M.Phil. in Computer Science and a Master’s in Statistics from Aligarh University. Prof. Hasan’s expertise spans Design & Analysis of Algorithms, E-Security, E-Learning, and Cloud Computing. With a career that began at Aligarh University, where he rose to the position of Professor & Head of Department, he later served as Professor & Head of IT Department at University of Technology and Applied Sciences in Oman. Prof. Hasan has supervised numerous PhD and Master’s students, authored 74 research papers, and played pivotal roles in academic leadership and research groups throughout his esteemed career.

🌐 Professional Profile:

Google Scholar

🎓 Academic Qualifications:

Ph.D. in Computer Science from Jamia Delhi (1994), M.Phil. (PGDCS) in Computer Science from Aligarh University (AMU, 1979), and Master’s in Statistics (1978) and Baccalaureate (1976) from Aligarh University, all with First Class distinctions.

🔍 Areas of Expertise:

Specializes in Design & Analysis of Algorithms, E-Security, E-Learning, and Cloud Computing.

👨‍🏫 Experience:

Began as a Lecturer at Aligarh University (1979-1994), progressing to Assistant Professor (1994-1995), Associate Professor (1995-1996), and Professor & Head of Department (1996-1997) at the same institution. Later, served as Professor & Head of IT Department at University of Technology and Applied Sciences (formerly Musanna College of Technology) in Oman (1997-2010), and currently as a Professor at King Abdulaziz University, Saudi Arabia (2010 – present), focusing on teaching, research, and academic administration.

🏆 Scholarly Achievements:

Actively supervises PhD and Master’s theses, having supervised over 30 Master’s dissertations. Published 74 research papers/articles and is a member of the Information Security Research Group at King Abdul-Aziz University. Founding Chairman of the Department of Computer Science at Aligarh Muslim University and Head of IT Department in Oman for 14 years.

Publication Top Notes:

 

 

Ms. Kritika | Cybersecurity Awards | Best Researcher Award

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Ms. Kritika | Cybersecurity Awards | Best Researcher Award

Ms. Kritika, India

🎓 Ms. Kritika, a dynamic Computer Science postgraduate 🖥️, holds both a Master’s and Bachelor’s degree from GGSIP University in New Delhi, India 🇮🇳. As an Independent Researcher based in Delhi, her expertise in cybersecurity is evident through her extensive contributions, including peer-reviewed articles and book chapters 📚. Kritika’s research interests span interdisciplinary cybersecurity domains, code smell detection in software 🧾, and vulnerability analysis and mitigation strategies 🛡️. Her ambition and dedication drive her to uncover new insights and best practices in the ever-evolving landscape of cybersecurity.

🌐 Professional Profile:

Orcid

🎓 Educational Background

  • Master of Technology in Computer Science and Engineering (2022) – GGSIP University, New Delhi, India
  • Bachelor of Technology in Information Technology (2019) – GGSIP University, New Delhi, India

🏢 Professional Experience

  • Independent Researcher – Delhi, India

📝 Research Interests

  • Interdisciplinary cybersecurity domains
  • Code smell detection in software
  • Vulnerability analysis and mitigation strategies

Publication Top Notes:

1.  Cyber Security and its cognitive ramifications on E-Governance
2.  Correlating propensity between code smell and vulnerability in java applications
3.  A Deep Dive into Code Smell and Vulnerability Using Machine Learning and Deep Learning Techniques
4.  A review on harmonizing psychological factors into cyber space
5.  Corollary of digital forensics in e governance

 

 

 

 

 

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. 🎓 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.” 🏅 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. 🔬 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 🎓

  • 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 🏅

  • 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 🔬

  • 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 📊

  • 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