Zhengyi Yao | Artificial Intelligence | Best Researcher Award

Published on by Cognitive Scientist Awards

Mr. Zhengyi Yao | Artificial Intelligence | Best Researcher Award

Sichuan Normal University |China

Zhengyi Yao, from Neijiang, Sichuan, China, is a dedicated researcher affiliated with Sichuan Normal University, holding both bachelor’s and master’s degrees in Computer Science and Technology. His work primarily focuses on the Internet of Things (IoT), cybersecurity, cryptography, and artificial intelligence (AI). With a growing presence in academic publishing, he has contributed to several high-impact journals indexed in SCI and Scopus. Mr. Yao has demonstrated a strong commitment to advancing secure, intelligent systems, particularly in logistics and industrial applications. His interdisciplinary approach blends theoretical research with practical implementation, contributing to emerging technologies such as blockchain-enabled IIoT and quantum cryptography. In addition to publishing five journal articles and securing seven patents, he actively contributes to the field through applied innovations aimed at enhancing privacy protection and data security. As a passionate technologist, Mr. Yao is continually exploring transformative solutions in smart systems, emphasizing the ethical and secure integration of AI in modern digital infrastructure.

Profile

Education

Zhengyi Yao completed his academic training at Sichuan Normal University, earning both his bachelor’s and master’s degrees in Computer Science and Technology. His undergraduate studies provided a solid foundation in software development, algorithms, and system architecture, while his postgraduate work emphasized advanced topics such as artificial intelligence, cybersecurity, and cryptographic methods. During his graduate years, he engaged deeply with interdisciplinary studies, aligning computer science with real-world applications in logistics, IoT, and secure communication systems. His academic performance has been marked by consistent excellence and a proactive engagement in research-driven projects. While enrolled, he also explored the practical aspects of emerging technologies, developing tools and frameworks to support digital transformation in industrial systems. His education has been instrumental in shaping his scientific outlook, fostering a commitment to ethical innovation and robust digital security. These academic experiences continue to inform his contributions to academic research and patent development in the tech and security domains.

Experience

Zhengyi Yao has gained substantial experience as a researcher and innovator in the fields of IoT, cybersecurity, cryptography, and AI. While at Sichuan Normal University, he actively participated in multiple collaborative research efforts that examined the integration of blockchain with IIoT systems and privacy-focused AI applications in logistics. Despite limited consultancy and editorial appointments, his practical contributions are demonstrated through five SCI/Scopus-indexed journal publications and seven patents. He has co-authored research tackling challenges in smart logistics security, 5G-based blockchain sensors, and quantum cryptography, showcasing his capability to bridge theoretical and applied computing. Through independent and team-driven efforts, Mr. Yao has contributed to designing secure systems that support data integrity and user privacy in dynamic industrial environments. His hands-on research experience, supported by solid academic training, underpins his drive to innovate in secure computing technologies and has positioned him as a promising young professional in China’s growing digital research landscape

Research Focus

Zhengyi Yao’s research centers on the intersection of emerging technologies like IoT, blockchain, AI, and cybersecurity, with a strong focus on intelligent logistics systems. He explores secure device communication, privacy-preserving data protocols, and cryptographic models for industrial systems. His work on blockchain-enabled IIoT platforms aims to fortify command operations against cyber threats, while his investigations into quantum cryptography are pushing the boundaries of next-generation digital security. One of his key contributions is the development of 5G-based universal blockchain smart sensors, combining speed, scalability, and trust for dynamic logistics applications. His research also examines how AI can be ethically and securely integrated into cyber-physical environments to optimize data flow, user privacy, and system integrity. Through published works and patented innovations, he is shaping solutions to critical security challenges facing smart logistics and industrial platforms. His forward-thinking approach promotes safer, more resilient infrastructures in an increasingly connected digital world.

Publications

Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System
Year: 2024
Citation:2

Blockchain-enabled device command operation security for Industrial Internet of Things
Year: 2023
Citation:12

5G-BSS: 5G-Based Universal Blockchain Smart Sensors
Year: 2022
Citation:2

Conclusion

Zhengyi Yao exemplifies the qualities of a dedicated and innovative researcher, with notable contributions to smart logistics, cybersecurity, and cryptographic technologies. His blend of academic rigor and applied invention positions him as a rising leader in secure digital systems.

Chongyuan Wang | Deep learning | Best Researcher Award

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Dr. Chongyuan Wang | Deep learning | Best Researcher Award

Dr. Chongyuan Wang, a Ph.D. researcher at Hohai University, specializes in artificial intelligence 🤖 and neural computation 🧠. He completed his B.S. at Jiangsu University 🇨🇳 and M.S. in Energy and Power from Warwick University 🇬🇧. His research journey is centered around biologically inspired learning algorithms, with notable contributions to dendritic neuron modeling and evolutionary optimization. Through innovative algorithms like Reinforced Dynamic-grouping Differential Evolution (RDE), Dr. Wang advances the understanding of synaptic plasticity in AI systems. His patent filings and international publications reflect a strong commitment to academic innovation and impact 🌍.

Profile

Education 🎓

🎓 B.S. in Engineering – Jiangsu University, China 🇨🇳
🎓 M.S. in Energy and Power – University of Warwick, UK 🇬🇧 (2018)
🎓 Ph.D. Candidate – Hohai University, majoring in Artificial Intelligence 🤖
Dr. Wang’s educational path bridges engineering and intelligent systems. His strong technical foundation and global exposure foster advanced thinking in machine learning and neuroscience. His current doctoral research integrates deep learning, dendritic neuron models, and biologically plausible architectures for improved learning accuracy and model efficiency. 📘🧠

Experience 👨‍🏫

Dr. Wang is currently pursuing his Ph.D. at Hohai University, where he investigates dendritic learning algorithms and synaptic modeling. 🧬 He proposed the RDE algorithm, enhancing dynamic learning in artificial neurons. His hands-on experience includes research design, algorithm optimization, patent writing, and international publication. He has contributed to projects such as “Toward Next-Generation Biologically Plausible Single Neuron Modeling” and “RADE for Lightweight Dendritic Learning.” 📊 His work balances theoretical depth and applied research, particularly in neural computation, classification systems, and resource-efficient AI. 🔬💡

Awards & Recognitions 🏅

🏅 Patent Holder (CN202410790312.0, CN202410646306.8, CN201510661212.9)
📄 Published in SCI-indexed journal Mathematics (MDPI)
🌐 Recognized on ORCID (0009-0002-6844-1446)
🧠 Nominee for Best Researcher Award 2025
His inventive research has earned him national patents and global visibility. His SCI publications in computational modeling reflect both novelty and academic rigor. His continued innovation in biologically inspired AI learning systems has established his position as an emerging researcher in intelligent systems. 🚀📘

Research Interests 🔬

Dr. Wang’s research fuses deep learning 🤖 and dendritic modeling 🧠 to create biologically plausible AI. He developed the RDE algorithm to mimic synaptic plasticity, improving convergence and adaptability in neural networks. His research areas include evolutionary optimization, adaptive grouping, resource-efficient models, and dendritic learning. He explores how artificial neurons can reflect real-brain behavior, leading to faster, more accurate AI systems. Current projects like RADE aim to make AI lightweight and biologically relevant. 🌱📊 His vision is to bridge the gap between neuroscience and AI through interpretable, high-performance algorithms. 🧠💡

Publications

  • Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model

    Mathematics
    2025-04-29 | Journal article
    DOI: 10.3390/math13091465
    CONTRIBUTORS: Chongyuan Wang; Huiyi Liu

Mansoor Ali Darazi | Artificial Intelligence | Best Researcher Award

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Dr. Mansoor Ali Darazi | Artificial Intelligence | Best Researcher Award

Dr. Mansoor Ali Darazi is an accomplished English language educator and researcher with extensive experience in ELT, curriculum development, and student mentorship. Passionate about modern pedagogical techniques, he fosters an inclusive learning environment while actively contributing to academic research. His expertise in language teaching, academic writing, and leadership roles has earned him recognition in the field. Committed to continuous professional growth, he participates in conferences and research projects. His dynamic teaching approach and strong managerial skills enhance students’ academic success and institutional development.

Profile

Education 🎓

Dr. Darazi is pursuing a Ph.D. in English Linguistics at the University of Sindh (2023–2026). He holds a Ph.D. in Education (ELT) (2022) and an M.Phil. in Education (ELT) (2014) from Iqra University, Karachi. He completed his Bachelor of Arts at Shah Abdul Latif University, Khairpur (1997). His academic journey reflects his dedication to English language teaching, research, and linguistic studies.

Experience 👨‍🏫

Dr. Darazi is an Assistant Professor at Benazir Bhutto Shaheed University, Lyari (2022–present). He has served as a Lecturer (2015–2022), ELT Coordinator, and English Lecturer at various institutions, including Army Public School, Pakistan Marine Academy, and Bahria Foundation College. With over two decades in academia, he has contributed to curriculum development, language instruction, and educational leadership, shaping student success through innovative teaching methodologies.

Awards & Recognitions 🏅

Dr. Darazi has received recognition for his contributions to education and research. His accolades include academic excellence awards, research grants, and honors from national and international organizations. His active participation in TESOL, IELTA, and Linguistic Society of America highlights his commitment to advancing English language education and pedagogy.

Research Interests 🔬

Dr. Darazi’s research explores English language proficiency, ELT methodologies, academic motivation, and student engagement. His publications address linguistic pedagogy, transformational leadership in education, and the role of feedback in language learning. His work contributes to developing innovative teaching strategies that enhance students’ academic performance and career prospects.

Publications