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.

Profile

Orcid

Scopus

🎓 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

Prof Dr. Yalan Ye | Artificial Intelligence | Best Researcher Award

Professor at University of Electronic Science and Technology of China, China.

Prof. Dr. Yalan Ye is a distinguished researcher and academic with expertise in artificial intelligence, particularly in intelligent information processing and computer application technology. She serves as a Professor and Doctoral Director at the University of Electronic Science and Technology of China, where she earned her bachelor’s, master’s, and doctoral degrees. Prof. Ye’s research focuses on multimodal data fusion, cognitive state identification, and generalization of perceptual models. She has a proven track record of success, with numerous publications in prestigious journals and conferences. Prof. Ye is also actively involved in consultancy and industry projects, demonstrating her ability to bridge academic research with real-world applications.

Professional Profiles:

- Scopus Profile
- ORCID Profile

Education

Prof. Dr. Yalan Ye received her bachelor’s, master’s, and doctoral degrees from the University of Electronic Science and Technology of China (UESTC). During her PhD studies, she participated in a joint training program at the University of California, Irvine, USA, under the supervision of IEEE Fellow Professor Chen-Yu Phillip Sheu. This joint training was funded by the China Scholarship Council.

Professional Experience

Prof. Dr. Yalan Ye is a distinguished professor and doctoral director in the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC). She has been deeply involved in the research of intelligent information processing methods and their applications for many years. Her expertise spans various areas of computer science, with a significant focus on artificial intelligence, intelligent information processing, and biomedical engineering. Prof. Ye has led numerous research projects, including 4 ongoing and 11 completed projects, and has contributed extensively to consultancy and industry-sponsored projects, with 14 such engagements to her credit. Her academic contributions include the publication of 68 journals in Scopus, authorship of a book, and holding 17 published patents with 9 more under process. Prof. Ye has also taken on significant editorial roles, such as chairman of ArtInHCI 2023, local chairman of ICITES 2021, and guest editor of Electronics. She has collaborated with notable professionals in her field, including IEEE/ACM/OSA Fellow Heng Tao Shen, and is an active member of IEEE.

Research Interest

Prof. Dr. Yalan Ye’s research interests encompass a broad range of topics within the realm of artificial intelligence and its applications. Her primary focus lies in the development and advancement of intelligent information processing methods. Specifically, she is dedicated to exploring computer application technology, artificial intelligence, and machine learning, with a particular emphasis on transfer learning, domain adaptation, and zero-shot learning. Additionally, Prof. Ye’s work delves into the biomedical engineering field, where she investigates the human state intelligence perception and cognition through multimodal data fusion. She is also committed to addressing challenging issues related to cognitive state identification, the generalization of perceptual models, and the stable identification of cognitive states. Her research has resulted in a series of internationally influential outcomes, featured in top-tier journals and conferences such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Multimedia, ACM Multimedia, IJCAI, ICASSP, and EMBC. Prof. Ye’s theoretical contributions have been widely cited and positively evaluated by numerous IEEE Fellows, including Prof. Yong Lian, a member of the Canadian Academy of Engineering and former president of the IEEE Circuits and Systems Society.

Award and Honors

Prof. Dr. Yalan Ye has received numerous awards and honors recognizing her outstanding contributions to artificial intelligence and intelligent information processing. She has earned Best Paper Awards at various international conferences for her innovative research papers on intelligent information processing and machine learning. Additionally, she has been honored with the Outstanding Researcher Award by her institution, the University of Electronic Science and Technology of China, for her significant contributions to computer science and engineering. Prof. Ye is also recognized as an IEEE Senior Member, a testament to her substantial achievements and expertise in electrical and electronics engineering. Furthermore, she has been awarded the China National Science Fund for Distinguished Young Scholars for her exceptional research capabilities and potential leadership in her field. Her research papers, highly cited in prominent journals and conferences, have made a significant impact on the scientific community, earning her the title of Top Cited Author. Prof. Ye has also served as a Guest Editor for special issues of leading journals and chaired several international conferences, such as ArtInHCI 2023 and ICITES 2021. Her collaborations with renowned IEEE/ACM/OSA Fellows further cement her status as a leading researcher in her field. Prof. Dr. Yalan Ye’s contributions have advanced the understanding and application of artificial intelligence, earning her respect and recognition from the global scientific community.

Research Skills

Prof. Dr. Yalan Ye excels in a wide range of research skills, particularly in artificial intelligence and intelligent information processing. Her expertise encompasses developing and applying machine learning algorithms, including transfer learning, domain adaptation, and zero-shot learning. She is adept at multimodal data fusion, enhancing cognitive state identification and model generalization. With a strong background in biomedical engineering, Prof. Ye applies AI to solve complex health problems. Her rigorous research methodologies and innovative solutions are reflected in her numerous publications in top-tier journals and conferences. Additionally, she has extensive experience in leading and managing academic and industry-sponsored research projects, showcasing her project management and collaborative research abilities.

Publications

Online multi-hypergraph fusion learning for cross-subject emotion recognition
- Authors: Pan, T., Ye, Y., Zhang, Y., Xiao, K., Cai, H.
- Year: 2024
- Citations: 0
Physiological Signal-Based Biometric Identification for Discovering and Identifying a New User
- Authors: Mu, X., Jiang, H., Li, F., Xiong, G., Ye, Y.
- Year: 2024
- Citations: 0
Online Unsupervised Domain Adaptation via Reducing Inter- and Intra-Domain Discrepancies
- Authors: Ye, Y., Pan, T., Meng, Q., Li, J., Shen, H.T.
- Year: 2024
- Citations: 1
Multimodal Physiological Signals Fusion for Online Emotion Recognition
- Authors: Pan, T., Ye, Y., Cai, H., Yang, Y., Wang, G.
- Year: 2023
- Citations: 0
Vibroarthrography-based Knee Lesions Location via Multi-Label Embedding Learning
- Authors: Pan, T., Zhang, Y., Dong, Q., Wan, Z., Ding, T.
- Year: 2023
- Citations: 0
Cross-subject EMG hand gesture recognition based on dynamic domain generalization
- Authors: Ye, Y., He, Y., Pan, T., Yuan, J., Zhou, W.
- Year: 2023
- Citations: 0
Cross-Subject Mental Fatigue Detection based on Separable Spatio-Temporal Feature Aggregation
- Authors: Ye, Y., He, Y., Huang, W., Wang, C., Wang, G.
- Year: 2023
- Citations: 1
Learning MLatent Representations for Generalized Zero-Shot Learning
- Authors: Ye, Y., Pan, T., Luo, T., Li, J., Shen, H.T.
- Year: 2023
- Citations: 5
Alleviating Style Sensitivity then Adapting: Source-free Domain Adaptation for Medical Image Segmentation
- Authors: Ye, Y., Liu, Z., Zhang, Y., Li, J., Shen, H.
- Year: 2022
- Citations: 3
ECG-based Cross-Subject Mental Stress Detection via Discriminative Clustering Enhanced Adversarial Domain Adaptation
- Authors: Ye, Y., Luo, T., Huang, W., Sun, Y., Li, L.
- Year: 2022
- Citations: 5

Cheng-Mao Zhou | Artificial intelligence | Best Researcher Award

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

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