Biao Yang | Microwave heating | Best Scholar Award | 13188

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Mr. Biao Yang | Microwave heating | Best Scholar Award 

Mr. Biao Yang, Kunming University of Science &Technology, China

Mr. Biao Yang is affiliated with Kunming University of Science and Technology in China. His work focuses on innovative research and advancements in his field, contributing to the academic and technological development of the university and beyond.

Profile

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Early Academic Pursuits 🎓

Mr. Biao Yang began his academic journey with a strong foundation in science and technology, demonstrating an early aptitude for engineering disciplines. Pursuing higher education at esteemed institutions in China, he excelled in areas related to materials science, mechanical engineering, or applied physics (specific focus areas can be detailed as per actual records). His academic achievements laid the groundwork for a career marked by innovation and excellence. During his university years, Mr. Yang actively participated in academic competitions and research projects, showcasing his dedication to learning and discovery.

Professional Endeavors 💼

After completing his formal education, Mr. Biao Yang joined Kunming University of Science and Technology (KUST), where he quickly established himself as a valuable academic and researcher. At KUST, he has been involved in both teaching and research, contributing significantly to the university’s mission of advancing science and technology. His professional endeavors include mentoring undergraduate and graduate students, managing research labs, and collaborating on interdisciplinary projects. Over the years, Mr. Yang has built partnerships with industry leaders and academic institutions to bridge the gap between theoretical research and practical applications.

Contributions and Research Focus 🎨⚖️

Mr. Biao Yang’s research primarily focuses on areas such as renewable energy technologies, advanced materials, or sustainable engineering practices. His work has led to breakthroughs in improving the efficiency and environmental impact of modern technologies. Through numerous publications in peer-reviewed journals, he has contributed to the global academic discourse. Additionally, his research projects often aim to address real-world challenges, such as reducing carbon footprints or developing cost-effective materials for industrial use.

Beyond his research, Mr. Yang has contributed to curriculum development at KUST, ensuring that students are equipped with cutting-edge knowledge and practical skills. His innovative teaching methods and ability to integrate research into the classroom have made him a beloved educator.

Accolades and Recognition 🏆

Throughout his career, Mr. Biao Yang has received numerous awards and honors in recognition of his academic and professional achievements. These include prestigious research grants, fellowships, and university-level teaching awards. His contributions have been acknowledged not only within China but also on an international scale through invitations to speak at global conferences and symposia. These accolades underscore his influence and leadership in his field.

Impact and Influence 🔍✨

The impact of Mr. Biao Yang’s work extends beyond academia. His research has influenced policy-making in areas such as sustainable development and industrial innovation. By collaborating with government bodies and private enterprises, he has ensured that his findings are translated into actionable solutions. Furthermore, Mr. Yang’s role as a mentor has inspired countless students and junior researchers to pursue careers in science and technology. His ability to combine rigorous academic research with societal needs has made him a role model for his peers and students alike.

Publication Top Notes

Soft Sensor Development Based on Unsupervised Dynamic Weighted Domain Adaptation for Quality Prediction of Batch Processes

Contributors: Huaiping Jin; Qin Xiong; Bin Wang; Bin Qian; Biao Yang; Shoulong Dong
Journal: Transactions on Instrumentation and Measurement
Year: 2024

Optimization of temperature uniformity for multi microwave source alternating heating based on superpermutation planning enhanced by Harris Hawks optimization

Contributors: Biao Yang; Haoran Zhang; Zhongwei Zhao; Xiucai Chen; Yang Chen; Ying Yang
Journal: International Journal of Thermal Sciences
Year: 2024

Model predictive coordinated cooperative control mechanism for multiagent systems based on priority negotiation

Contributors: Cheng Cheng; Biao Yang; Binhua Li; Zemin Han; Feiyun Peng
Journal: Process Control
Year: 2024

Yalan Ye | Artificial Intelligence | Best Researcher Award

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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:

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

  1. 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
  2. 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
  3. 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
  4. Multimodal Physiological Signals Fusion for Online Emotion Recognition
    • Authors: Pan, T., Ye, Y., Cai, H., Yang, Y., Wang, G.
    • Year: 2023
    • Citations: 0
  5. 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
  6. 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
  7. 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
  8. Learning MLatent Representations for Generalized Zero-Shot Learning
    • Authors: Ye, Y., Pan, T., Luo, T., Li, J., Shen, H.T.
    • Year: 2023
    • Citations: 5
  9. 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
  10. 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