Zhang Shuaitong prospective Assistant Professor
Disciplines: Biomedical Engineering, Artificial Intelligence
Direction: Medical image analysis; Research on Artificial Intelligence Algorithms
E-mail :zhangshuaitong@bit.edu.cn
Office Address: Room 411, No.7 Teaching Building, Beijing Institute of Technology, No.5 Zhongguancun South Street, Haidian District, Beijing
Shuaitong Zhang is a pre-appointed assistant Professor (Special Associate Researcher) at the Beijing Institute of Technology. Since I began my doctoral study in 2015, I have been engaged in the quantitative analysis of medical images based on artificial intelligence for the difficulties in the clinical diagnosis and treatment of diseases such as brain tumors and esophageal cancer. His main research interests include the segmentation and classification of medical images based on artificial intelligence, and its application in the diagnosis and treatment of brain tumors and esophageal cancer. As the first author (including co-first author) in npj Precision Oncology, European Radiology, Annals of Surgical Oncology, More than 10 papers have been published in international authoritative Journal conferences such as Journal of MRI. This work was supported by EurekAlert!, a global science news platform hosted by the American Association for the Advancement of Science (AAAS). And reprinted by science news outlets such as new wise and medical Xpress. Participate in the development of an expert consensus of the Chinese Medical Association as a co-developer of expert consensus. Hosted a national Nature Youth Fund and participated in 3 projects.

Research on Medical Image Analysis Based on Artificial Intelligence
Algorithm research: Aiming at the problems such as small sample size, long-tail distribution and data island faced by medical image analysis tasks, the accuracy of medical image segmentation and classification tasks is improved through innovative deep learning algorithms such as semi-supervised and prototype learning.
Applied research: In view of the difficulties encountered in the clinical diagnosis and treatment of tumors, methods such as imaging omics or deep learning are used to quantitatively analyze medical images to assist in solving clinical problems such as accurate preoperative diagnosis of tumors or evaluation of therapeutic effects.

2015-09 to 2020-07, Institute of Automation, University of Chinese Academy of Sciences, Computer Application Technology, PhD;
2011-09 to 2015-06, Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, B.S.

2015-09 to 2020-07, Institute of Automation, University of Chinese Academy of Sciences, Computer Application Technology, PhD;
2011-09 to 2015-06, Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, B.S.
2023-03-present, pre-appointed Assistant Professor (Special Associate Researcher), School of Medical Technology, Beijing Institute of Technology;
2020-07 to 2023-02, Postdoc, School of Medical Science and Engineering, Beijing University of Aeronautics and Astronautics, Co-supervisor: Professor Fan Yobo