Dr. Zhe Yuan | Deep Learning Awards | Best Researcher Award

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Dr. Zhe Yuan | Deep Learning Awards | Best Researcher Award 

Dr. Zhe Yuan, xidian University, China

Zhe Yuan is a Ph.D. student at Xidian University, Xi’an, Shaanxi, specializing in cutting-edge research in image processing, small object detection using deep learning, and unmanned aerial vehicle (UAV) technology. He earned his Master’s degree from Shaanxi University of Technology (2019-2022) and has industry experience as a Testing Engineer at TPRI (2022-2023). His research contributions include pioneering techniques for small target detection in UAV remote sensing images, emphasizing advanced multi-scale fusion attention mechanisms and adaptive weighted feature fusion. Zhe has published multiple influential works in renowned journals, such as Remote Sensing, and collaborated on projects addressing dynamic electromagnetic forces in water-lubricated bearings, showcasing his interdisciplinary expertise. His innovative research has been cited and recognized internationally, reinforcing his position as a promising researcher in his field.

Professional Profile:

SCOPUS

ORCID

Suitability for the Research for Best Researcher Award

Zhe Yuan has demonstrated exceptional contributions to fields such as image processing, small object detection using deep learning, and UAV technology. His research showcases a clear focus on impactful and innovative solutions, aligning well with the criteria for the Research for Best Researcher Award. Below is a summary of his suitability.

Education 🎓

  • Ph.D. Student (2023/09–Present): Xidian University
  • Testing Engineer (2022/06–2023/07): TPRI
  • Master’s Degree (2019/09–2022/06): Shaanxi University of Technology

Research Directions 🔬

  • Image Processing 🖼️
  • Small Object Detection Using Deep Learning 🤖
  • Unmanned Aerial Vehicle (UAV) Technology 🚁

Publication top Notes:

Dynamic variation mechanism of electromagnetic force for loading device of water⁃lubricated bearing

Small Object Detection in UAV Remote Sensing Images Based on Intra-Group Multi-Scale Fusion Attention and Adaptive Weighted Feature Fusion Mechanism

YuanZ,NWang,Wang P,et al. Research on Non- contact Electromagnetic Loading Device for Water- lubricated Bear ng[J]. Journal of Physics: Conference Series, 2020, 1624(6):062020 (7pp).

Dynamic electromagnetic force variation mechanism and energy loss of a non-contact loading device for a water-lubricated bearing

Research on Non-contact Electromagnetic Loading Device for Water-lubricated Bearing

Assoc Prof Dr. Wenlong Hang | Artificial Intelligence Award | Best Researcher Award

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Assoc Prof Dr. Wenlong Hang | Artificial Intelligence Award | Best Researcher Award

Assoc Prof Dr. Wenlong Hang, Nanjing Tech University, China

Wenlong Hang holds a Doctor of Engineering degree from Jiangnan University, where he graduated in June 2017, specializing in Light Industry Information Technology. During his doctoral studies, he visited both Hong Kong Polytechnic University and the Shenzhen Institutes of Advanced Technology. Since September 2017, Dr. Hang has been a faculty member at the School of Computer Science and Technology at Nanjing Tech University. His research interests primarily focus on artificial intelligence and machine learning, with a particular emphasis on medical image analysis and EEG signal processing. He has published more than 30 papers in reputable journals and conferences, contributing significantly to semi-supervised learning, federated learning, and EEG classification techniques. His representative works include research on medical image segmentation, reliability-aware semi-supervised frameworks, and domain-generalized EEG classification.

Professional Profile:

Summary of Suitability for Best Researcher Award :

Wenlong Hang is highly suitable for the Best Researcher Award based on his extensive research and contributions in the fields of artificial intelligence, machine learning, and medical image processing. His academic background, with a Doctor of Engineering degree from Jiangnan University, and professional experiences at institutions like Hong Kong Polytechnic University and Shenzhen Institutes of Advanced Technology, demonstrates his deep involvement in advanced technological research.

Education:

  • Doctor of Engineering (Graduated in June 2017)
    • Major: Light Industry Information Technology
    • Institution: Jiangnan University
    • Doctoral Visits: Hong Kong Polytechnic University, Shenzhen Institutes of Advanced Technology

Work Experience:

  • Since September 2017: Faculty Member
    • Position: Professor at the School of Computer Science and Technology
    • Institution: Nanjing Tech University

Research Areas:

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Medical Image Segmentation
  • EEG Classification

Publication top Notes:

CITED: 109
CITED: 109
CITED: 73
CITED: 67
CITED: 34
CITED: 33