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.

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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

GCSTormer: Gated swin transformer with channel weights for image denoising

Contributors: Minling Zhu; Zhixin Xu; Qi Zhang; Yonglin Liu; Dongbing Gu; Sendren Shengdong Xu

Journal: Expert Systems with Applications

Year: 2025

Generative Adversarial Networks With Noise Optimization and Pyramid Coordinate Attention for Robust Image Denoising

Contributors: Min‐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

Contributors: Minling Zhu; En Kong

Journal: Electronics

Year: 2024

Lilei Sun | Artificial intelligence | Best Researcher Award | 13305

Posted on 17/03/202517/03/2025 by sciencefather

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.

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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

Dual structure-aware consensus graph learning for incomplete multi-view clustering

Contributors: Lilei Sun; Wai Keung Wong; Yusen Fu; Jie Wen; Mu Li; Yuwu Lu; Lunke Fei

Journal: Pattern Recognition

Year: 2025

Balance guided incomplete multi-view spectral clustering

Contributors: Lilei Sun; Jie Wen; Chengliang Liu; Lunke Fei; Lusi Li

Journal: Neural Networks

Year: 2023

Two‐view attention‐guided convolutional neural network for mammographic image classification

Contributors: Lilei Sun; Jie Wen; Junqian Wang; Yong Zhao; Bob Zhang; Jian Wu; Yong Xu

Journal: CAAI Transactions on Intelligence Technology

Year: 2023

Cheng-Mao Zhou | Artificial intelligence | Best Researcher Award

Posted on 06/12/202406/12/2024 by sciencefather

Dr. Cheng-Mao Zhou | Artificial intelligence | Best Researcher Award

Dr. Cheng-Mao Zhou, Central People’s Hospital of Zhanjiang, China

Dr. Cheng-Mao Zhou is a distinguished medical professional affiliated with the Central People’s Hospital of Zhanjiang, China. With extensive expertise in clinical practice and research, Dr. Zhou specializes in advancing patient care through innovative medical treatments and health management strategies. His contributions to the medical field reflect a commitment to excellence and the well-being of his community.

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🎓 Educational Qualification

Dr. Cheng-Mao Zhou’s academic journey is deeply rooted in a passion for innovation and excellence in medical science. From his formative years, he demonstrated an extraordinary aptitude for problem-solving and an eagerness to explore the intersection of technology and healthcare. His early academic focus on applied research set the foundation for his current expertise in artificial intelligence (AI) and perioperative medicine. By integrating traditional medical practices with emerging AI technologies, Dr. Zhou carved out a unique niche, positioning himself as a leader in predictive healthcare solutions.

🩺 Professional Endeavors

Currently serving at the Central People’s Hospital of Zhanjiang, Dr. Zhou has applied his expertise to revolutionize perioperative care. His professional trajectory reflects a seamless blend of clinical practice and research, where he employs machine learning and deep learning algorithms to address critical challenges in postoperative complication prediction and prevention. Over the years, he has developed and implemented cutting-edge AI models that significantly enhance diagnostic accuracy and patient outcomes, making complex healthcare processes more efficient and reliable.

🧠 Contributions and Research Focus

Dr. Zhou’s research centers on leveraging artificial intelligence to solve pressing issues in perioperative medicine. His focus areas include:

Postoperative Complication Prediction
Integration of AI in Medicine
Educational Contributions

🏆 Accolades and Recognition

Dr. Zhou’s dedication and contributions have not gone unnoticed. Among his many affiliations, his membership with esteemed organizations like the American Society for Honorary Scientific Research (Sigma Xi) and the Big Data Group of Anesthesiology Branch of the Chinese Medical Association underscore his credibility and influence. Furthermore, his position as a young member of the Comfort Medical Branch of the China Cardiovascular Anesthesia Society reflects his commitment to advancing comfort-focused medical practices.

His academic contributions have been recognized in prestigious journals, with 40 publications indexed in SCI and Scopus. His citation index of 13 highlights the scholarly impact of his work on the global research community.

🌟 Impact and Influence

Dr. Zhou’s influence transcends the realm of academia. His innovative methodologies have significantly enhanced clinical practices, offering a roadmap for integrating AI into everyday medical care. By addressing critical challenges such as delayed diagnoses and suboptimal postoperative management, his work has led to improved patient safety and healthcare efficiency.

Through his articles and clinical implementations, Dr. Zhou has effectively raised awareness about the practical potential of AI in medicine, inspiring fellow researchers and healthcare practitioners to adopt data-driven solutions. His contributions serve as a blueprint for hospitals and medical institutions aiming to optimize their operational processes through technology.

🌍 Legacy and Future Contributions

Dr. Zhou envisions a future where AI seamlessly integrates with medical systems to revolutionize patient care worldwide. His ongoing research projects aim to further refine AI algorithms for predicting and preventing a broader range of complications. Beyond innovation, he is committed to mentoring young researchers, fostering interdisciplinary collaborations, and advocating for ethical AI practices in medicine.

📝Publication Top Notes

Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology.

Contributors: Zhou CM; Wang Y; Yang JJ; Zhu Y

Journal: BMC medical informatics and decision making

Year: 2023

Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms.

Contributors: Chengmao Zhou; Wang Y; Xue Q; Zhu Y

Journal: Cancer control

Year: 2023

Machine learning predicts lymph node metastasis of poorly differentiated-type intramucosal gastric cancer

Contributors: Zhou, C.-M.; Wang, Y.; Ye, H.-T.; Yan, S.; Ji, M.; Liu, P.; Yang, J.-J.

Journal: Scientific Reports

Year: 2021

Morteza Karimian Kelishadrokhi | Artificial Intelligence | Best Researcher Award

Posted on 18/06/202419/06/2024 by sciencefather

Mr. Morteza Karimian Kelishadrokhi | Artificial Intelligence | Best Researcher Award

Deep Learning Researcher at Islamic Azad University (IAU) Najafabad Branch, Iran.

Morteza Karimian Kelishadrokhi is a distinguished researcher specializing in artificial intelligence and data science, holding a master’s degree in Artificial Intelligence from Islamic Azad University (IAU), Najafabad Branch, Iran. He excels in deep learning, focusing on EEG signal analysis and time series classification. Morteza is recognized for his development of advanced neural network architectures, including memory-augmented models, to enhance the classification of brain activities. His research extends to signal processing and computer vision, where he explores novel techniques for content-based image retrieval and real-time data analysis. Morteza’s contributions significantly advance AI methodologies, impacting both academic research and practical applications across various industries. His dedication and expertise position him as a key figure in the field, bridging theoretical advancements with tangible solutions in artificial intelligence and data-driven technologies.

Professional Profiles:

Education

Morteza Karimian Kelishadrokhi holds a Master of Science in Artificial Intelligence from the Islamic Azad University (IAU), Najafabad Branch, Iran, graduating in 2024. He excelled academically, achieving first place among students of the computer faculty with an outstanding GPA of 19.42 out of 20.00. His dedication and excellence were recognized by the dean, who honored him as the “Top Scientific Student.” Morteza also holds a Bachelor of Science in Computer Science from the same institution, graduating in 2021. During his undergraduate studies, he secured first place in the academic year 2019-2020 and second place in 2018-2019. Additionally, he served as a Teaching Assistant for the “Deep Learning Course” in both the Fall and Winter semesters of 2021 and 2022. Morteza’s educational journey highlights his exceptional academic performance and strong focus on artificial intelligence and deep learning.

Professional Experience

Morteza Karimian Kelishadrokhi is a Deep Learning Researcher and Senior Data Analyst at the Islamic Azad University (IAU), Najafabad Branch, Iran. He coordinates with industries and participates in workshops, such as the “Application of Deep Learning in the Industry.” Morteza has contributed to various research projects, including the development of a Security Framework for AI-Enhanced Microarchitectural Analysis and a Multi-Class EEG Brain Activity Classification system using the TD-MANN architecture. He has served as a Teaching Assistant for the “Deep Learning Course” in the Fall and Winter semesters of 2021 and 2022, where he designed course materials and assisted students with projects. Morteza’s work also extends to consultancy and industry projects, applying his expertise in AI, machine learning, and data analytics to solve real-world problems. His professional journey is marked by innovative research and practical applications in artificial intelligence.

Research Interest

Morteza Karimian Kelishadrokhi’s research interests span several cutting-edge domains within artificial intelligence and data science. He is particularly focused on deep learning, exploring its applications in time series classification and EEG signal analysis. His work aims to develop advanced neural network architectures, such as memory-augmented neural networks, to improve the classification of brain activities. Additionally, Morteza is interested in signal processing and computer vision, seeking innovative solutions for content-based image retrieval and real-time data analysis. His research contributes to the advancement of AI methodologies and their practical implementation in various scientific and industrial applications.

Award and Honors

Morteza Karimian Kelishadrokhi has received multiple accolades for his academic excellence and contributions to the field of artificial intelligence. In 2022, he was honored and awarded by the dean of the Islamic Azad University, Najafabad branch, as the “Top Scientific Student.” He secured the 1st place position in the academic years 2019-2020 and 2018-2019, and 2nd place in the academic year 2018-2019. Additionally, Morteza has served as a teaching assistant for the “Deep Learning Course” during the winter semester of 2022 and the fall semester of 2021. He also played a key role in coordinating with industries and participating as a speaker in the workshop “Application of Deep Learning in the Industry” in 2022.

Research Skills

Morteza Karimian Kelishadrokhi possesses a diverse skill set in research methodologies and advanced data analysis. His expertise includes developing and implementing deep learning models, particularly for EEG signal classification and time series analysis. He is proficient in designing neural network architectures, including memory-augmented neural networks, and applying machine learning algorithms to solve complex problems. Morteza is skilled in signal processing techniques and has experience with computer vision applications, such as content-based image retrieval. His research capabilities extend to conducting comprehensive literature reviews, data preprocessing, and statistical analysis, ensuring the integrity and reliability of his findings. Additionally, he is adept at using various programming languages and tools essential for AI research, including Python, TensorFlow, and MATLAB.