JIA Xibin

JIA Xibin serves as a full Professor and doctoral/master's thesis supervisor at Beijing University of Technology's Faculty of Information Technology and Dublin International College. She holds editorial responsibilities for the TIIS journal and maintains active memberships in the China Computer Federation (CCF) and China Society of Image and Graphics (CSIG), including specialized committees for Machine Vision and Big Video Data.

Her educational foundation spans a B.S. in Wireless Technology from Chongqing University (1991), M.S. in Measuring and Testing Technology from North University of China (1996), and Ph.D. in Computer Application Technology from Beijing University of Technology (2007). International experience includes visiting scholar positions at University of California Riverside (2015) and Flinders University (2009).

Research focuses on intelligent medical imaging for liver disease diagnosis, affective computing in educational contexts, and cognitive behavior modeling through multimodal fusion techniques. Her methodology integrates representation learning with transfer and few-shot learning paradigms to address data scarcity in medical applications.

Current publications demonstrate consistent focus on domain adaptation and medical image analysis, with significant contributions to multimodal MRI interpretation for non-alcoholic fatty liver disease and hepatocellular carcinoma. Her work bridges theoretical machine learning with clinical applications through deep neural network architectures.

Active research leadership includes principal investigator roles for:

• National Natural Science Foundation grant on non-invasive liver disease assessment (2019-2022)
• Beijing Natural Science Foundation project on campus safety risk prediction (2020-2022)

These projects emphasize big data analytics for healthcare and educational safety systems, reflecting her dual expertise in technical innovation and practical implementation.