Dr. Ling Li | Information Security | Best Researcher Award

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Dr. Ling Li | Information Security | Best Researcher Award

Dr. Ling Li, University of Electronic Science and Technology of China, China

Dr. Ling Li is an accomplished researcher at the University of Electronic Science and Technology of China, specializing in cyberspace security and advanced AI techniques. With a Ph.D. in Cyberspace Security and a strong academic foundation, Dr. Li has made significant contributions to the fields of cloud-edge computing, federated learning, and 6G network security. Her research has garnered attention for its innovative approaches to privacy protection, data cleaning, and multi-task scheduling in heterogeneous edge networks. She has published extensively in top-tier journals and conferences and holds multiple patents in the field. Dr. Li’s work continues to shape the future of secure, intelligent network systems, and she is recognized for her leadership in advancing next-generation technologies. 🚀

Professional Profile:

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Suitability for the Award

Dr. Ling Li is highly suitable for the Best Researcher Award due to her pioneering contributions to cybersecurity, federated learning, and network security. Her innovative work on improving model accuracy and privacy in non-IID environments, as well as her advancements in 6G network security, position her as a leader in these cutting-edge fields. With several high-impact publications, multiple patents, and leadership roles in national projects, Dr. Li has demonstrated excellence in both research and practical applications. Her continuous efforts to push the boundaries of secure and intelligent network systems make her an ideal candidate for this prestigious award. 🏅

Education

🎓 Dr. Ling Li holds a Ph.D. in Cyberspace Security from the University of Electronic Science and Technology of China, where she specialized in cybersecurity and intelligent network systems. Before pursuing her Ph.D., she earned her Master’s degree from Southwest Jiaotong University, laying the groundwork for her research in network security and artificial intelligence. Her academic journey has been focused on blending theoretical knowledge with practical applications, particularly in the areas of privacy protection and federated learning. Dr. Li’s education has provided a strong foundation for her innovative contributions to the rapidly evolving field of cybersecurity and intelligent systems. 📘

Experience

Dr. Li has extensive academic and research experience, currently serving as a key researcher at the University of Electronic Science and Technology of China. She leads cutting-edge projects on cloud-edge computing, federated learning, and 6G network security. Her expertise has made her a pivotal figure in the development of innovative approaches for enhancing privacy protection in non-IID environments. Dr. Li has also been involved in key national projects, including a Central Universities Foundation initiative and a National Natural Science Foundation project, where she serves as a lead researcher. Her experience spans across cybersecurity, AI, and data analytics, making her a leading expert in these domains. 🌐

Awards and Honors

🏆 Dr. Ling Li’s exceptional research has earned her several honors, including recognition for her groundbreaking work in federated learning and network security. She has published multiple SCI/EI-indexed papers in prestigious journals such as MDPI Sensors and Frontiers of Computer Science, and presented at major conferences like IJCNN and ISNCC. Additionally, Dr. Li holds three Chinese invention patents, underscoring her innovation in the field. Her leadership in national and university-level projects has positioned her as a trailblazer in her field, contributing significantly to the advancement of cybersecurity and intelligent network systems. 🎖️

Research Focus

🔍 Dr. Li’s research focus lies at the intersection of cybersecurity, artificial intelligence, and intelligent network systems. She has pioneered new methods in cloud-edge-end federated learning to improve model accuracy and privacy protection, particularly in non-IID environments. Her work extends to the development of statistical relational learning techniques for automatic data cleaning and repair. Furthermore, Dr. Li is at the forefront of 6G network security research, with a focus on privacy protection and multi-task scheduling optimization in heterogeneous edge networks. Her contributions have significant implications for the future of secure, intelligent networks. 🌟

Publication Top Note:

Title: Cloud–Edge–End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments
Year: 2024

 

 

 

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) 🔢

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:

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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

 

 

Prof. Muhammad Abuturab | cryptosystem Awards | Best Researcher Award

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Prof. Muhammad Abuturab | cryptosystem Awards | Best Researcher Award

Prof. Muhammad Abuturab , Maulana Azad National Urdu University , India

Professor Muhammad Rafiq Abuturab is currently a Professor at the Department of Physics, Maulana Azad National Urdu University, Hyderabad, India. With a specialization in optical information processing, optical signal processing, and digital holography, his research focuses on advanced cryptosystems and computational imaging techniques. He has an impressive academic career, having served in various capacities at institutions like the Muzaffarpur Institute of Technology and Maulana Azad College of Engineering and Technology. Prof. Abuturab has collaborated internationally with scholars like Prof. Ayman Alfalou from France and Prof. Zhengjun Liu from China. He has published extensively, with significant citations and a notable h-index, reflecting his impact in the field. His educational background includes a Ph.D. in Physics and a Post-Doctoral Fellowship at ISEN Brest, France. Prof. Abuturab is also proficient in teaching subjects such as optics, quantum mechanics, and electromagnetic theory.

Professional Profile:

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🎓Education:

Professor Muhammad Rafiq Abuturab holds a Ph.D. in Physics from M. U., India. He further advanced his expertise through a Post-Doctoral Fellowship at LABISEN–Yncréa Ouest (Yncréa-Ouest Research Laboratory), ISEN Brest, France.

🏢Work Experience:

Professor Muhammad Rafiq Abuturab is currently a Professor at Maulana Azad National Urdu University in Hyderabad, India, a position he has held since November 1, 2023. Prior to this, he served as an Associate Professor at Muzaffarpur Institute of Technology in Muzaffarpur, India, from September 9, 2022, to October 31, 2023. Before his tenure there, he was an Assistant Professor at Maulana Azad College of Engineering and Technology in Patna, India, from January 1, 2010, to September 8, 2022. Additionally, he worked as a Senior Lecturer at the same institution from February 8, 2009, to December 31, 2009.

🏆Awards:

Professor Muhammad Rafiq Abuturab has made significant contributions to his field through numerous publications, which have garnered significant citations and a notable h-index, reflecting his impactful research. He has also engaged in international collaborations with esteemed scholars such as Prof. Ayman Alfalou from France and Prof. Zhengjun Liu from China, further enhancing the reach and influence of his work.

Publication Top Notes:

  • Multiple color image fusion, compression, and encryption using compressive sensing, chaotic-biometric keys, and optical fractional Fourier transform
  • Securing multiple-single-channel color image using unequal spectrum decomposition and 2D-SLIM biometric keys
  • Coherent superposition based single-channel color image encryption using gamma distribution and biometric phase keys
    • Conference: Pattern Recognition and Tracking XXXII
    • Year: 2021
    • Date: 2021-04-12
    • DOI: 10.1117/12.2586814
    • Contributors: Muhammad Rafiq Abuturab
  • A superposition based multiple-image encryption using Fresnel-Domain high dimension chaotic phase encoding
    • Journal: Optics and Lasers in Engineering
    • Year: 2020
    • Contributors: Muhammad Rafiq Abuturab
  • Multiple information fusion and encryption using DWT and Yang-Gu mixture amplitude-phase retrieval algorithm in fractional Fourier domain
    • Conference: 4th International Conference on Soft Computing: Theories and Applications (SoCTA 2019), Proceedings of SoCTA, Advances in Intelligent Systems and Computing, Springer
    • Year: 2020
    • Contributors: Muhammad Rafiq Abuturab