Li Zhang | Blockchain | Best Researcher Award

Dr. Li Zhang | Blockchain | Best Researcher Award

Dr. Li Zhang – lecturer, Guilin University of Electronic Technology, China.

Zhang Li is a dedicated researcher and lecturer in the School of Computer and Information Security at Guilin University of Electronic Technology. With a strong academic foundation in computer science and engineering, she has carved a niche in blockchain, Internet of Things (IoT), and consensus algorithms. Zhang has published multiple top-tier SCI journal articles and holds innovative patents in wireless blockchain technologies. She actively contributes to peer reviews for international conferences and journals. Her work reflects both deep theoretical knowledge and practical innovation, establishing her as a promising figure in next-generation distributed computing technologies.

Publication Profile

Scopus

Education Background

Zhang Li earned her Doctor of Engineering in Computer Application Technology in 2024 from the University of Chinese Academy of Sciences, specializing in blockchain and IoT. She completed her Master’s degree in Computer Software and Theory at Beijing Normal University in 2018 and received her Bachelor’s in Information and Computing Science from Hainan Normal University in 2015. Her educational journey showcases a solid blend of mathematics, software theory, and advanced computer applications, laying a robust foundation for her current research contributions in blockchain consensus mechanisms and wireless computing architectures.

Professional Experience

Zhang Li began her academic career as a lecturer in July 2024 at the School of Computer and Information Security, Guilin University of Electronic Technology. During her doctoral years, she was involved in high-impact national research projects and provided assistance in grant writing and paper reviews. She contributed to the National Natural Science Foundation project on mobile crowd sensing from 2019 to 2022. As a conference and journal reviewer, she brings rigorous analytical insights to global platforms. Her professional trajectory reflects a seamless integration of academic leadership, collaborative research, and technical expertise.

Awards and Honors

While formal awards are not specifically listed, Zhang Li’s achievements include publishing in top SCI Zone 1 journals such as IEEE Transactions on Wireless Communications and IEEE Internet of Things Journal, each with impact factors exceeding 10. She is a recognized contributor to national-level funded research and has received recognition for her patent contributions under substantial examination. Additionally, her roles as a reviewer for IEEE GLOBECOM and The Journal of Supercomputing further emphasize her scholarly impact in the global research community.

Research Focus

Zhang Li focuses on blockchain consensus protocols, particularly within IoT environments and wireless networks. Her research includes designing scalable and reliable consensus mechanisms, developing smart contracts, and exploring zero-knowledge proofs for data security. She has addressed complex challenges such as byzantine fault tolerance and committee-based consensus for multi-hop wireless networks. Zhang also investigates encryption algorithms and communication protocols, contributing to the broader field of secure distributed systems. Her work combines theoretical innovation with application relevance, making her a key contributor in blockchain-based networking technologies.

Publications

  1. An efficient and reliable byzantine fault tolerant blockchain consensus protocol for single-hop wireless networks
    Published in:  2024
    Cited by: 14 articles

  2. Scalable Creditable-Committee-based Blockchain Consensus Protocol for Multi-Hop Wireless Networks
    Published in:  2024
    Cited by: 5 articles

  3. A blockchain-based computing architecture for mobile ad-hoc cloud
    Published in:  2020
    Cited by: 17 articles

Conclusion

Zhang Li exemplifies academic excellence, innovative research, and emerging leadership in computer science. Her deep expertise in blockchain and IoT applications, validated by high-impact publications and patents, aligns with the cutting-edge demands of secure wireless systems. She demonstrates admirable qualities such as optimism, teamwork, and dedication to continuous learning and teaching. With a strong sense of collaboration and scientific rigor, Zhang Li is well-positioned to drive transformative change in the digital and distributed computing landscape.

Dr. Waeal Obidallah | Blockchain Technology | Best Researcher Award

Dr. Waeal Obidallah | Blockchain Technology | Best Researcher Award

Assistant Professor, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Dr. Waeal J. Obidallah 🌍 is a dynamic researcher and academician with over a decade of expertise in both corporate and academic realms. With a rich blend of experience in digital transformation, machine learning, data mining, and electronic business technologies, Dr. Obidallah has continually driven innovative outcomes in every role he has undertaken. Known for his leadership in guiding cross-functional teams and for his analytical mindset, he seamlessly bridges the gap between research theory and practical application. His inspiring approach, commitment to growth, and passion for pushing boundaries make him a prominent figure in the fields of digital innovation and intelligent systems.

Publication Profile

🎓 Education Background

Dr. Obidallah earned his Ph.D. in Digital Transformation and Innovation from the University of Ottawa, Canada 🇨🇦 (2014–2021), where he developed cutting-edge expertise in leveraging technology for transformative change. He previously completed his MSc in Electronic Business Technologies at the same university (2011–2013), equipping him with a solid foundation in the digital economy, e-commerce, and business intelligence systems.

💼 Professional Experience

Currently serving as an Assistant Professor at the Imam Mohammad ibn Saud Islamic University in Riyadh, Saudi Arabia 🇸🇦 since 2021, Dr. Obidallah has been instrumental in shaping curriculum and guiding research in the College of Computer and Information Sciences, Department of Information Systems. His professional background includes leading interdisciplinary teams in both academia and industry, delivering data-driven solutions and high-impact publications.

🏅 Awards and Honors

While no individual awards are listed, Dr. Obidallah’s profile is marked by significant academic impact 📈, evidenced by over 100+ citations, 54 co-authors, and contributions to renowned international journals. His consistent scholarly output reflects recognition and respect within the global research community.

🔬 Research Focus

Dr. Obidallah’s research focuses on Digital Transformation, Data and Text Mining, Machine Learning, FinTech, Blockchain, and Big Data 📊. He is especially interested in applying AI and data science techniques to enhance intelligent systems, industrial operations, medical sensors, and smart environments. His work also incorporates Design Science Research Methodology (DSRM) to structure innovation with academic rigor.

🧩 Conclusion

A lifelong learner and dedicated innovator, Dr. Waeal Obidallah continues to influence the evolving landscape of data-driven technologies with his deep expertise and enthusiastic leadership. 🚀 His unwavering pursuit of excellence, coupled with his motivational spirit, has made him a role model for aspiring researchers and collaborators alike. Embracing challenges beyond the comfort zone, he is committed to making impactful contributions in the ever-changing digital world.

📚 Top Publication Notes

Quantum computational infusion in extreme learning machines for early multi-cancer detectionJournal of Big Data, 2025
Cited by: 1 | This innovative article explores the fusion of quantum computing with ELMs to revolutionize early cancer diagnostics.

Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environmentsScientific Reports, 2025
Cited by: 2 | A comprehensive study of deep learning models designed for predictive maintenance in limited-resource industrial setups.

AI-based energy aware parent selection mechanism to enhance security and energy efficiency for smart homes in IoTExpert Systems, 2025
A novel AI-powered method optimizing security and energy in IoT home systems.
DOI: 10.1111/exsy.13647

Beyond the hype: A TAM-based analysis of blockchain adoption drivers in construction industryHeliyon, 2024
Offers insights into real-world blockchain adoption using the Technology Acceptance Model (TAM).
DOI: 10.1016/j.heliyon.2024.e38522

Ensuring the integrity assessment of IoT medical sensors using hesitant fuzzy setsHealth Informatics Journal, 2024
Focuses on trustworthy IoT applications in healthcare via fuzzy logic.
DOI: 10.1177/14604582241301019

Intelligent Reconfigurable Surface Assisted Constellation Index Selection Spatial Modulation Over Nakagami-m Fading ChannelsIEEE Access, 2024
Technical exploration of smart communication channels with reconfigurable surfaces.
DOI: 10.1109/ACCESS.2024.3455998