Junying Chen

Junying Chen is the senior member of IEEE, China Computer Federation, China Society of Image and Graphics, and Chinese Society of Biomedical Engineering. She is also the member of IEEE-HKN, IEEE-CIS, AAAI, MICCAI, and ACL. She is the assistant director of the Key Laboratory of Big Data and Intelligent Robot of the Ministry of Education, and a core member of the research team of intelligent software and robots in South China University of Technology. She mainly engages in scientific research in medical ultrasound imaging, intelligent image processing, deep learning fundamental research, high-performance computing, etc. She is the principal investigator of 1 National Natural Science Foundation of China project, 4 Guangdong Natural Science Foundation projects, 1 Guangzhou Science and Technology Program project, 1 National Key Laboratory open project, and 3 Fundamental Research Funds for Central Universities projects, and participates in a number of national, ministerial, and provincial key research projects. She published more than 40 papers in academic journals and conferences, applied for 10 invention patents (including 4 PCT patents), authorized more than 20 software copyrights, published 2 books, and received the Second Prize for Technological Invention from China Computer Federation Science and Technology Award and Second Prize of Excellent Papers of Guangdong Computer Academy.

Education Background

• 2007-2013 Ph.D. in Electrical and Electronic Engineering, The University of Hong Kong (Supervisors: Hayden K.-H. So & Victor O. K. Li)
• 2003-2007 B.E. in Electronic Information Engineering (Outstanding Graduates), Zhejiang University

Working Experience

• Since 2019 Assistant Director of the Key Laboratory of Big Data and Intelligent Robot, Ministry of Education
• Since 2017 Associate Professor with School of Software Engineering, South China University of Technology
• 2013-2017 Assistant Professor with School of Software Engineering, South China University of Technology

Research Interests

Deep learning algorithms and architectures, Pattern recognition, Medical ultrasound imaging, Medical image segmentation and intelligent diagnosis, Multi-modal image data fusion, Multi-modal text and image data analysis, Heterogeneous parallel acceleration and analysis.