Shoujun Zhou | Digital Signatures | Best Scholar Award

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Prof. Shoujun Zhou | Digital Signatures | Best Scholar Award

Research professor at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

Prof. Shoujun Zhou is a distinguished researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, and a double researcher at the National High Performance Medical Device Research Institute. He received his Ph.D. in Biomedical Engineering from Southern Medical University in 2004. With extensive experience in interventional surgical robotics and medical imaging, Prof. Zhou has led numerous significant research projects, including four National Natural Science Foundation projects and a major instrument project. He has been recognized for his contributions to science and technology, receiving awards such as the first prize for Science and Technology Progress from the Ministry of Education and the Silver Award at the Global Medical Robot Innovation Design Competition. A prolific author, he has published over 100 scientific papers and holds more than 60 patents. Prof. Zhou is also actively involved in various professional committees and organizations related to medical technology and innovation.

Profile:

Education:

Prof. Shoujun Zhou obtained his Ph.D. in Biomedical Engineering from Southern Medical University in July 2004. Prior to that, he earned his Master’s degree in Communication and Information Systems from Lanzhou University in July 2000. His academic journey began with a Bachelor’s degree in Test and Control, which he completed at the Air Force Engineering University in July 1993. This strong educational foundation has equipped him with a deep understanding of biomedical engineering, communication systems, and control technologies, paving the way for his distinguished research career.

Professional Experience:

Prof. Shoujun Zhou has had a distinguished career in biomedical engineering and medical device research. Since October 2010, he has served as a Distinguished Researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, where he focuses on interventional surgical robotics and image-guided therapy. Prior to this role, he worked as a Senior Engineer in the Information Department of the 458th Hospital of the People’s Liberation Army from May 2008 to August 2010. He also completed a postdoctoral fellowship at the School of Information Engineering, Beijing Institute of Technology, from August 2004 to March 2007. Additionally, he held a postdoctoral position at Shenzhen Haibo Technology Co., Ltd., from May 2007 to August 2008 and served as an engineer in the PLA 94921 Unit from July 1993 to August 2001. Throughout his career, Prof. Zhou has contributed to numerous high-impact research projects, demonstrating his expertise in advanced medical technologies.

Research Interests:

Prof. Shoujun Zhou specializes in the fields of interventional surgical robotics and medical imaging. His primary research interests include the development of advanced image-guided therapy techniques, focusing on improving the precision and effectiveness of surgical interventions. He is particularly dedicated to the design and application of intelligent interventional robotic systems, integrating artificial intelligence to enhance decision-making and operational efficiency in surgical procedures. Additionally, Prof. Zhou explores medical image processing methodologies, aiming to innovate techniques that optimize the visualization and analysis of complex medical data. His work significantly contributes to the advancement of minimally invasive surgical approaches and the integration of robotics in healthcare.

Skills:

Prof. Shoujun Zhou possesses a robust skill set in biomedical engineering, specializing in interventional surgical robotics and medical imaging. He has expertise in designing and implementing advanced robotic systems for surgical applications, with a focus on image-guided therapy. Prof. Zhou is proficient in artificial intelligence algorithms and their integration into medical devices, enhancing surgical precision and patient outcomes. His technical skills include medical image processing, algorithm development, and system optimization, complemented by a strong background in project management and leadership. Additionally, he is experienced in conducting multidisciplinary research, collaborating with healthcare professionals and engineers to drive innovations in medical technology.

Conclusion:

Prof. Shoujun Zhou’s extensive research background, numerous awards, and significant contributions to the fields of surgical robotics and medical imaging make him an exceptional candidate for the Research for Best Scholar Award. His work not only advances technology in medicine but also improves patient outcomes through innovative solutions. His leadership in various high-impact projects and dedication to research excellence underscore his suitability for this prestigious recognition.

Publication Top Noted:

  • Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation
    • Journal: Bioengineering
    • Publication Date: 2024-10-15
    • DOI: 10.3390/bioengineering11101031
    • Contributors: Zhiqing Zhang, Tianyong Liu, Guojia Fan, Yao Pu, Bin Li, Xingyu Chen, Qianjin Feng, Shoujun Zhou
  • Automatic Delineation of the 3D Left Atrium From LGE-MRI: Actor-Critic Based Detection and Semi-Supervised Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2024-06
    • DOI: 10.1109/JBHI.2024.3373127
    • Contributors: Shun Xiang, Nana Li, Yuanquan Wang, Shoujun Zhou, Jin Wei, Shuo Li
  • SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2024-05
    • DOI: 10.1109/JBHI.2024.3370864
    • Contributors: Kai-Ni Wang, Sheng-Xiao Li, Zhenyu Bu, Fu-Xing Zhao, Guang-Quan Zhou, Shou-Jun Zhou, Yang Chen
  • SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation
    • Journal: IEEE Transactions on Medical Imaging
    • Publication Date: 2024-04
    • DOI: 10.1109/TMI.2023.3336534
    • Contributors: Juzheng Miao, Si-Ping Zhou, Guang-Quan Zhou, Kai-Ni Wang, Meng Yang, Shoujun Zhou, Yang Chen
  • A Fast Actuated Soft Gripper Based on Shape Memory Alloy Wires
    • Journal: Smart Materials and Structures
    • Publication Date: 2024-04-01
    • DOI: 10.1088/1361-665X/ad2f0c
    • Contributors: Xiaozheng Li, Yongxian Ma, Chuang Wu, Youzhan Wang, Shoujun Zhou, Xing Gao, Chongjing Cao
  • An Adaptive Control Method and Learning Strategy for Ultrasound-Guided Puncture Robot
    • Journal: Electronics
    • Publication Date: 2024-01-31
    • DOI: 10.3390/electronics13030580
    • Contributors: Tao Li, Quan Zeng, Jinbiao Li, Cheng Qian, Hanmei Yu, Jian Lu, Yi Zhang, Shoujun Zhou
  • A Precise Calibration Method for the Robot-Assisted Percutaneous Puncture System
    • Journal: Electronics
    • Publication Date: 2023-12-01
    • DOI: 10.3390/electronics12234857
    • Contributors: Jinbiao Li, Minghui Li, Quan Zeng, Cheng Qian, Tao Li, Shoujun Zhou
  • Online Hard Patch Mining Using Shape Models and Bandit Algorithm for Multi-Organ Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2022-06
    • DOI: 10.1109/JBHI.2021.3136597
    • Contributors: Jianan He, Guangquan Zhou, Shoujun Zhou, Yang Chen
  • To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information
    • Journal: BioMed Research International
    • Publication Date: 2020-07-11
    • DOI: 10.1155/2020/5615371
    • Contributors: Shibin Wu, Pin He, Shaode Yu, Shoujun Zhou, Jun Xia, Yaoqin Xie
  • Cerebrovascular Segmentation from TOF-MRA Using Model- and Data-Driven Method via Sparse Labels
    • Journal: Neurocomputing
    • Publication Date: 2020-03
    • DOI: 10.1016/j.neucom.2019.10.092
    • Contributors: Baochang Zhang, Shuting Liu, Shoujun Zhou, Jian Yang, Cheng Wang, Na Li, Zonghan Wu, Jun Xia