Lubin Wang | Computer Science | Best Researcher Award

Mr. Lubin Wang | Computer Science | Best Researcher Award

Guilin Institute of Information Technology | China

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🎓 Early Academic Pursuits

Mr. Lubin Wang began his academic journey with a Bachelor's degree in Computer Science and Technology at Shanxi Datong University. His early years were marked by active engagement in software development projects, where he not only served as a core developer but also honed critical skills in modular design, teamwork, and leadership. His proactive involvement in both academic and extracurricular technology initiatives laid a strong foundation for his future research career. Notably, he contributed to an open-source database management tool on GitHub that garnered over 2.4k stars, reflecting early promise and innovation.

💼 Professional Endeavors

Following his undergraduate studies, Mr. Wang advanced his expertise by enrolling in a Master's program at Guilin University of Technology, in collaboration with the National Space Science Center of the Chinese Academy of Sciences. Throughout this period, he managed several interdisciplinary projects in high-tech domains including IoT, aerospace data systems, and smart manufacturing. As a project lead and software manager, Mr. Wang took charge of planning, coordinating, and executing complex software systems, displaying not only technical aptitude but also remarkable project governance.

🧠 Contributions and Research Focus

Mr. Wang’s research spans a diverse set of domains unified by a core theme—intelligent systems and automation. He spearheaded the design and implementation of a cloud-based smart printing factory platform that combined neural networks with physical control systems, achieving near-perfect detection accuracy. In the realm of smart cities, he developed a novel traffic-responsive lighting control algorithm and integrated it into a robust management platform supported by SpringBoot and MQTT protocols. His contributions to wind turbine diagnostics involved developing MATLAB-based reliability models, while his work on smart oil testing platforms showcased expertise in OCR, blockchain, and predictive analytics.

🏅 Accolades and Recognition

Mr. Wang has earned numerous accolades that reflect his academic excellence and technical mastery. He secured the First Prize at the National College Student English Vocabulary Challenge in both 2022 and 2023 and was recognized in various programming and language competitions. His academic performance also earned him prestigious scholarships and awards throughout his graduate studies. Beyond these formal recognitions, his influence extends to the online education community, where his Bilibili content channel has amassed thousands of views, demonstrating his ability to communicate complex ideas to broader audiences.

🌍 Impact and Influence

The practical impact of Mr. Wang’s work is far-reaching. His innovations in smart factory and city infrastructure have been piloted at major institutions, contributing to automation, safety, and efficiency. His software and hardware solutions have influenced how industrial faults are detected and managed, while his academic guidance has helped numerous graduate students succeed in their entrance examinations. Mr. Wang’s ability to bridge theory with real-world applications underscores his role as both a thinker and a doer in the field of intelligent systems.

🔮 Legacy and Future Contributions

Looking ahead, Mr. Wang is positioned to continue making transformative contributions to the fields of artificial intelligence, urban computing, and autonomous control systems. His trajectory suggests not only sustained innovation but also leadership in shaping the future of intelligent infrastructure and research-led development. As a mentor, researcher, and technology developer, Mr. Wang is building a legacy defined by curiosity, excellence, and a profound commitment to technological advancement.

Publications


📘 HYFF-CB: Hybrid Feature Fusion Visual Model for Cargo Boxes

Authors: Juedong Li, Kaifan Yang, Cheng Qiu, Lubin Wang, Yujia Cai, Hailan Wei, Qiang Yu, Peng Huang
Journal: Sensors
Year: 2025


📗 BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection

Authors: Long Guo, Lubin Wang (陆斌 王), Qiang Yu, Xiaolan Xie
Journal: Applied Sciences
Year: 2024


📙 DYNet: A Printed Book Detection Model Using Dual Kernel Neural Networks

Authors: Lubin Wang (陆斌 王), Xiaolan Xie, Peng Huang, Qiang Yu
Journal: Sensors
Year: 2023


Hongfei Yang | Engineering | Best Researcher Award

Assoc Prof Dr. Hongfei Yang | Engineering | Best Researcher Award

Shihezi University | China

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🌱 Early Academic Pursuits

Dr. Hongfei Yang’s academic journey is marked by an impressive foundation in engineering and scientific disciplines. He earned his Bachelor's degree in Mechanical Design, Manufacturing, and Automation from Dalian University in 2016. Following this, he pursued his Master’s in Mechanical Design and Theory at Jilin University, complemented by a joint training program at Cambridge University. These early years laid a solid groundwork in mechanical design, equipping him with a unique blend of theoretical knowledge and practical skills.

💼 Professional Endeavors

Currently an Associate Professor in Electronic Information Engineering at Shihezi University, Dr. Yang has dedicated his career to advancing precision engineering and measurement technology. His experience includes a rigorous doctoral program in Testing and Measurement Technology at Jilin University, where he focused on developing innovative solutions in instrument technology. Dr. Yang's professional path reflects his commitment to impactful research and teaching in electronic and mechanical engineering fields.

📚 Contributions and Research Focus

Dr. Yang’s research is distinguished by its focus on magnetic sensing and machine vision, especially in applications for unstructured environments and deep-earth observations. As the first author of 11 academic papers with a cumulative impact factor of 59.4, he has made substantial contributions to journals like IEEE Transactions on Geoscience and Remote Sensing and IEEE Sensors Journal. His work addresses pressing challenges in instrument measurement, such as developing methods for identifying rail defects and creating robust magnetic sensing systems. His expertise extends to multiple patents, demonstrating practical solutions for applications ranging from long-term monitoring in extreme environments to automated mushroom collection devices.

🏆 Accolades and Recognition

Dr. Yang’s contributions have been recognized with numerous honors. Among them are the prestigious National Scholarship for Doctoral Students in China, awarded by the Ministry of Education, and Jilin University's First-Class Doctoral Excellence Scholarship. His scholarly achievements and dedication have earned him the title of "Outstanding Graduate" and the Geological Instrument Scholarship from Jilin University. These accolades reflect his exceptional research performance and his ongoing impact in his field.

🌍 Impact and Influence

Dr. Yang’s influence extends beyond academia, as he actively participates in shaping engineering knowledge as a reviewer for top journals like IEEE Transactions on Instrumentation and Measurement. His work on projects, such as the National Natural Science Foundation of China project on environmental recognition for engineering vehicles, has pushed the boundaries of how advanced data processing can improve machine vision in complex environments. His contributions to deep borehole observation technology are advancing our understanding of deep-earth environments, with applications in various scientific and industrial domains.

🏅 Legacy and Future Contributions

Dr. Yang’s career represents a blend of innovation, interdisciplinary expertise, and real-world applications. His research in precision engineering, machine vision, and magnetic sensing continues to inspire advancements in technology and scientific exploration. His legacy lies in both his published works and his commitment to teaching, mentoring, and advancing engineering research. Looking forward, Dr. Yang is set to further enrich the field of electronic information engineering, leaving an enduring impact on the next generation of scientists and engineers.

 

Publications


📝 SwinLabNet: Jujube Orchard Drivable Area Segmentation Based on Lightweight CNN-Transformer Architecture

Authors: Mingxia Liang, Longpeng Ding, Jiangchun Chen, Liming Xu, Xinjie Wang, Jingbin Li, Hongfei Yang
Journal: Agriculture
Year: 2024


📝 Neural Network-Based 3D Point Cloud Detection of Targets in Unstructured Environments

Authors: D. Wang, H. Yang, Z. Yao, Z. Chang, Y. Wang
Journal: Advances in Mechanical Engineering
Year: 2024


📝 MI-FPD: Magnetic Information of Free Precession Signal Data Measurement Method for Bell-Bloom Magnetometer

Authors: D. Bai, L. Cheng, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2024


📝 Efficient Measurement of Free Precession Frequency in Bell-Bloom Atomic Magnetometers

Authors: D. Bai, Y. Zhou, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Instrumentation and Measurement
Year: 2024


📝 EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application

Authors: J. Hu, H. Yang, J. He, D. Bai, H. Chen
Journal: IEEE Access
Year: 2024


 

Fan Wang | Engineering | Best Researcher Award

Dr. Fan Wang | Engineering | Best Researcher Award

Nanjing University of Information Science and Technology | China

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Early Academic Pursuits

Dr. Fan Wang's academic journey commenced with a Bachelor of Science in Mathematics from Hefei Normal University, China. This foundational education laid the groundwork for her subsequent pursuit of higher studies. She then pursued a Master's degree at the School of Mathematics, Southeast University, Nanjing, China, followed by a Doctor of Science degree, further specializing in Mathematics.

Professional Endeavors

Dr. Wang's professional endeavors reflect a global engagement with various esteemed academic institutions. She has held research positions at prominent universities such as the University of Macau, the University of Hong Kong, and Southeast University in China. Additionally, she has enriched her academic experience through international collaborations, serving as a Visiting PhD Student at Brunel University London, UK, and an Alexander von Humboldt Research Fellow at the University of Duisburg-Essen, Germany.

Contributions and Research Focus

Dr. Wang's research primarily focuses on advanced topics in control theory, with a specialization in two-dimensional systems and sensor networks. Her contributions encompass robust control and filtering techniques, distributed filtering over wireless sensor networks, and state estimation for networked systems with incomplete information. Through her publications in esteemed journals and conferences, she has significantly advanced the understanding and application of these techniques in real-world scenarios.

Accolades and Recognition

Dr. Wang's dedication and contributions to the field have been recognized through various awards and honors. Notably, she received the prestigious Alexander von Humboldt Research Fellowship of Germany in 2020 and has been acknowledged as an Excellent Reviewer of Neurocomputing in 2023. Her outstanding contributions to research have consistently earned her recognition from peers and institutions alike.

Impact and Influence

Dr. Wang's research has made a significant impact on the field of control theory and related disciplines. Her work on recursive filtering, robust state estimation, and protocol-based control has contributed to advancing the state-of-the-art in handling complex systems with limited information and communication constraints. Her findings have practical implications across diverse domains, including engineering, automation, and information technology.

Legacy and Future Contributions

Dr. Wang's legacy lies in her pioneering research and dedication to advancing the frontiers of control theory. Her work serves as a foundation for future researchers in the field, offering insights and methodologies that can address emerging challenges in complex system analysis and control. Her commitment to excellence and interdisciplinary collaboration ensures that her contributions will continue to shape the landscape of control theory and its applications in the years to come.

Notable publications

Recursive filtering for two-dimensional systems with amplify-and-forward relays: Handling degraded measurements and dynamic biases 2024

Finite-Horizon H State Estimation for Complex Networks With Uncertain Couplings and Packet Losses: Handling Amplify-and-Forward Relays 2023

Distributed Fusion Filtering for Nonlinear Time-Varying Systems Over Amplify-and-Forward Relay Networks: An H Quantized Framework 2023 (1)

Recursive locally minimum-variance filtering for two-dimensional systems: When dynamic quantization effect meets random sensor failure 2023 (5)

Robust set-membership filtering for two-dimensional systems with sensor saturation under the Round-Robin protocol 2022 (33)

 

 

 

Nam-Phuong Tran | Computer Science | Best Researcher Award

Mr. Nam-Phuong Tran | Computer Science | Best Researcher Award

Chung-Ang University | South Korea

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Early Academic Pursuits

Mr. Nam-Phuong Tran began his academic journey at Hanoi University of Science and Technology, Vietnam, where he pursued a Bachelor of Engineering in Computer Science, completing it from August 2015 to June 2020. His thesis, "Spatio-Temporal Dynamics of the Labor Market," showcased his early dedication to research. Subsequently, he pursued an MSc of Science in Computer Science at Chung-Ang University, Seoul, Korea, focusing on QoE Management for Video Streaming Systems over IRS-aided RSMA Networks under the guidance of Professor Sungrae Cho.

Professional Endeavors

Tran has diversified professional experience, ranging from software engineering to research roles. He worked as a Software Engineer at Viettel Digital Service and as a Graduate Research Assistant at the Ultra-Intelligent Computing/Communication Lab, Chung-Ang University. Additionally, he has served as a Software Developer, Data Scientist Intern, and Undergraduate Research Assistant, gaining exposure to various facets of computer science and engineering.

Contributions and Research Focus

Tran's research primarily revolves around improving Quality of Experience (QoE) in communication networks, focusing on topics such as wireless resource allocation, bitrate adaptation, and low-latency protocols. His expertise spans intelligent reflecting surfaces, rate-splitting multiple access, IoT, deep learning, reinforcement learning, federated learning, and multimedia over wireless networks. He has also delved into big data analytics, including data crawling, mining, visualization, and predictive analytics.

Accolades and Recognition

Tran's dedication to academia has been acknowledged through numerous awards and scholarships, including the Chung-Ang University Young Scientist Scholarship, Brain Korea 21 Graduate School Research Scholarship, Daewoong AI Big Data Scholarship, and the Shinhan Bank Scholarship. He has also received recognition for his programming skills and outstanding thesis presentation.

Impact and Influence

Tran's research contributions, particularly in the realm of improving QoE in communication systems, have the potential to influence the development of more efficient and user-centric network protocols. His work in wireless resource allocation, bitrate adaptation, and low-latency protocols could lead to significant advancements in multimedia streaming, IoT, and metaverse applications, shaping the future of communication technologies.

Legacy and Future Contributions

Tran's legacy may lie in his interdisciplinary approach to addressing challenges in communication networks and big data analytics. His research outputs and professional endeavors are poised to contribute to advancements in wireless communication, machine learning applications, and data-driven decision-making. With his demonstrated commitment to excellence and innovation, he is likely to continue making notable contributions to the field of computer science and engineering, both in academia and industry.

Notable Publications

Joint wireless resource allocation and bitrate adaptation for QoE improvement in IRS-aided RSMA-enabled IoMT streaming systems 2024

Privacy-Preserving Traffic Flow Prediction: A Split Learning Approach 2023

Delay-constrained quality maximization in RSMA-based video streaming networks 2022

A Survey on Intelligent Reflecting Surface-aided Non-Orthogonal Multiple Access Networks 2022

A Survey on Passive Beamforming using Statistical State Information in Intelligent Reflecting Surface Assisted Networks 2022