Minling Zhu | Artificial Intelligence | Best Researcher Award | 13405

Assoc Prof Dr. Minling Zhu | Artificial Intelligence | Best Researcher Award 

Assoc Prof Dr. Minling Zhu, Beijing Information Science and Technology University, China

Assoc. Prof. Dr. Minling Zhu is an esteemed faculty member at the College of Computer Science, Beijing Information Science and Technology University, China. She earned her Ph.D. from Beihang University in 2012 and has since made significant contributions to the fields of Artificial Intelligence and Embedded Systems. A Senior Member of the Chinese Association for Artificial Intelligence and a member of several key national technical and educational committees, Dr. Zhu plays an active role in shaping China’s AI research and smart education development.

Profile

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🌱 Early Academic Pursuits

Assoc. Prof. Dr. Minling Zhu began her academic journey with a passion for computational systems and intelligent technologies. Her formative years were characterized by a deep curiosity in how machines learn and interact with real-world environments. This passion led her to pursue advanced studies in computer science, culminating in a Ph.D. from Beihang University, one of China’s most prestigious institutions in engineering and technology, in 2012. During her doctoral research, she laid the foundation for her future exploration into Artificial Intelligence (AI) and Embedded Systems, gaining both theoretical expertise and practical acumen.

🧑‍🏫 Professional Endeavors

Following the completion of her doctoral degree, Dr. Zhu joined the College of Computer Science at Beijing Information Science and Technology University (BISTU) as an Associate Professor. In this role, she has been actively involved in both undergraduate and postgraduate teaching, contributing significantly to the university’s mission of nurturing the next generation of AI and embedded systems professionals.

Dr. Zhu is also engaged in administrative, curriculum development, and mentoring activities, embodying the values of academic leadership and institutional development. She consistently integrates cutting-edge research into her classroom, ensuring that students benefit from real-time technological progress.

🔬 Contributions and Research Focus

Dr. Minling Zhu’s research work stands at the intersection of Artificial Intelligence and Embedded Systems, two rapidly evolving domains with transformative potential. Her scholarly interests span:

  • Intelligent computation and adaptive systems

  • Machine learning algorithms and applications

  • Real-time processing in embedded platforms

  • AI-driven smart education systems

Her work aims to make AI more accessible and functional within embedded environments, contributing to smarter and more efficient systems in fields such as robotics, automation, and smart learning platforms.

Through the integration of embedded technology and intelligent algorithms, Dr. Zhu’s research not only advances theoretical models but also impacts practical applications in real-world scenarios.

🏆 Accolades and Recognition

Dr. Zhu’s contributions to the academic and research community have been widely acknowledged:

  • She is a Senior Member of the Chinese Association for Artificial Intelligence (CAAI), a prestigious role that reflects her depth of expertise and ongoing contributions to the field.

  • She serves as a Member of the Smart Education Professional Committee in China, working on innovative intersections between AI and modern pedagogy.

  • Additionally, she is a member of the Chinese National Technical Committee on Information Technology Standardization, where she contributes to national-level strategic standards in emerging technologies.

These roles position her not only as a researcher but also as a national thought leader in AI and educational technology.

🌍 Impact and Influence

The impact of Dr. Zhu’s work is far-reaching. Her research has contributed to:

  • Enhancing intelligent learning systems, providing personalized education experiences

  • Improving the efficiency of embedded AI, essential for mobile and IoT applications

  • Shaping national policies and standards that will guide China’s digital infrastructure for years to come

Her influence extends through her students and collaborators, many of whom have gone on to build careers in research, technology, and education—spreading the effects of her mentorship far beyond the university.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Zhu aims to further her research in human-centric AI systems, autonomous learning environments, and next-generation embedded solutions. She continues to mentor young researchers and lead collaborative initiatives both nationally and internationally.

Her legacy will be marked not only by her scholarly publications and technical contributions but also by her role in empowering young innovators to embrace AI and embedded systems for the betterment of society.

As AI and embedded technologies continue to reshape the digital world, Dr. Minling Zhu’s ongoing research and leadership ensure she remains at the forefront of innovation, guiding technological progress with intellectual rigor, visionary foresight, and social responsibility.

Publication Top Notes

ContributorsMinling Zhu; Zhixin Xu; Qi Zhang; Yonglin Liu; Dongbing Gu; Sendren Shengdong Xu
Journal: Expert Systems with Applications

Year: 2025

ContributorsMin‐Ling Zhu; Jia‐Hua Yuan; En Kong; Liang‐Liang Zhao; Li Xiao; Dong‐Bing Gu; Alexander Hošovský
Journal: International Journal of Intelligent Systems
Year: 2025

Multi-Scale Fusion Uncrewed Aerial Vehicle Detection Based on RT-DETR

ContributorsMinling Zhu; En Kong
Journal: Electronics
Year: 2024

Lilei Sun | Artificial intelligence | Best Researcher Award | 13305

Assist. Prof. Dr. Lilei Sun | Artificial intelligence | Best Researcher Award 

Assist. Prof. Dr. Lilei Sun, Guizhou Minzu University, China

Prof. Dr. Lilei Sun is an associate professor at Guizhou Minzu University, China, specializing in deep learning, image processing, pattern recognition, and medical image processing. He completed his B.E. in computer technology in 2016 and obtained his Ph.D. in software engineering in 2022, both from Guizhou University, Guiyang. Dr. Sun’s research focuses on incomplete multi-view clustering and has led to notable contributions in academic publications, including 10 articles in prestigious journals. He serves as an associate editor for the International Journal of Image and Graphics and is actively involved in collaborative research projects.

Profile

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🌱 Early Academic Pursuits

Prof. Dr. Lilei Sun began his academic journey with a solid foundation in computer technology. He received his B.E. degree in Computer Technology from Guizhou University in Guiyang, China, in 2016. This laid the groundwork for his advanced studies in software engineering, a field that has had a significant impact on his subsequent research. His academic excellence and curiosity drove him to pursue a Ph.D. in Software Engineering from Guizhou University, which he successfully completed in 2022. Throughout his academic journey, he consistently demonstrated a deep passion for understanding the intricacies of deep learning, image processing, and pattern recognition, as well as their transformative potential in medical image processing. 🌟

🔬 Professional Endeavors and Contributions

Since 2024, Prof. Dr. Sun has been serving as an Associate Professor at Guizhou Minzu University, where he has made notable strides in both teaching and research. In his role, he mentors students and collaborates with fellow researchers on projects that explore cutting-edge technologies in deep learning and image processing. His contributions to the academic community extend beyond the classroom as he actively participates in various consultancy projects and industry collaborations, applying his research to real-world problems. Dr. Sun’s work has led to practical innovations in the fields of medical image processing and pattern recognition, areas that are increasingly critical for advancing healthcare solutions globally. 🏥

💡 Research Focus

Prof. Dr. Sun’s research interests revolve around deep learning, image processing, pattern recognition, and medical image processing. One of his key areas of focus is incomplete multi-view clustering, a method that enables more accurate data analysis in scenarios where information is incomplete or fragmented. This has potential applications in various fields, including healthcare, where the integration of multi-source medical data can lead to better diagnostic models and more personalized treatments. Additionally, his work on medical image processing leverages machine learning techniques to enhance the quality and accuracy of medical imaging, providing practitioners with more reliable diagnostic tools. The potential to save lives and improve healthcare outcomes makes this research both significant and timely. 🔍

🏆 Accolades and Recognition

Prof. Dr. Sun has garnered recognition for his dedication to both teaching and research. He has published 10 academic articles, many of which have been featured in respected journals indexed by SCI and Scopus. He is also an associate editor of the International Journal of Image and Graphics, a prestigious journal that underscores his expertise in the field. His work has earned him an esteemed position in the academic community, further enhanced by his ongoing contributions to industry projects and collaborations. Through his research, Prof. Dr. Sun has received significant acknowledgment from his peers, with numerous invitations to speak at international conferences and collaborate with experts from various research institutes globally. 🌍

🌟 Impact and Influence

Prof. Dr. Sun’s work has had a profound impact on the fields of image processing and medical image processing. His research on deep learning and pattern recognition has contributed to advancements in the way medical data is processed, interpreted, and used in clinical decision-making. His innovations are poised to help healthcare providers access more accurate, timely, and comprehensive information, ultimately leading to improved patient outcomes. Furthermore, his involvement in professional memberships and editorial boards for various scientific journals has allowed him to influence the direction of research in his areas of expertise. 📊

💫 Legacy and Future Contributions

As Prof. Dr. Sun continues his research journey, his legacy is beginning to take shape through his groundbreaking contributions to deep learning and medical image processing. His passion for exploring innovative solutions to real-world challenges, particularly in healthcare, positions him as a leader in his field. In the coming years, Prof. Dr. Sun aims to push the boundaries of incomplete multi-view clustering, further developing techniques that can be applied across multiple domains, including medical diagnostics, artificial intelligence, and big data analytics. His commitment to excellence in research, teaching, and mentorship will continue to inspire future generations of students and researchers.

Publications Top Notes

Contributors: Lilei Sun; Wai Keung Wong; Yusen Fu; Jie Wen; Mu Li; Yuwu Lu; Lunke Fei
Journal: Pattern Recognition
Year: 2025
ContributorsLilei Sun; Jie Wen; Chengliang Liu; Lunke Fei; Lusi Li
Journal: Neural Networks
Year: 2023
Contributors: Lilei Sun; Jie Wen; Junqian Wang; Yong Zhao; Bob Zhang; Jian Wu; Yong Xu
Journal: CAAI Transactions on Intelligence Technology
Year: 2023