Jiyang Dong is a Professor and Doctoral Supervisor at the School of Electronic Science and Engineering, Xiamen University. He also holds a concurrent appointment as Professor and Doctoral Supervisor at the National Institute for Data Science in Health and Medicine (at the School of Medicine), Xiamen University. He received his Ph.D. from Xiamen University in 2001 and subsequently conducted postdoctoral research at the Institute of Electronic Engineering, Xidian University, under the supervision of Professor Zheng Bao, Academician of the Chinese Academy of Sciences. He joined Xiamen University as a faculty member in January 2004. He has also conducted visiting research at the University of Cambridge, the University of Washington, and Hong Kong Baptist University. These experiences have shaped his interdisciplinary research background spanning electronic information, physics, analytical chemistry, mass spectrometry, and biomedical data analysis.

Professor Dong has long been engaged in biomedical signal processing, metabolomics data analysis, and multimodal biomedical data modeling. His research interests include machine learning, spatial multi-omics, computational mass spectrometry, mass spectrometry imaging, molecular network modeling, and health and medical big data. Focusing on major diseases such as Alzheimer’s disease, hepatocellular carcinoma, diabetic kidney disease, nasopharyngeal carcinoma, and gastric cancer, he and his team have developed methods for metabolic network analysis, spatial metabolomics analysis, mass spectrometry imaging data processing, omics data integration, and machine learning modeling. These methods are used to characterize metabolic abnormalities, spatial heterogeneity, and molecular interactions during disease development and progression. His research emphasizes the integration of methodological development with validation in real biomedical samples, with the aim of extracting biologically meaningful and clinically relevant information from complex omics data.

In recent years, Professor Dong has led multiple projects funded by the National Natural Science Foundation of China and Fujian Province. He has published more than 160 papers in leading journals, including Angew. Chem. Int. Ed., Adv. Sci., Anal. Chem., Anal. Chim. Acta, and Brief. Bioinform. His research takes biomedical signals and omics data as its main objects of study, and uses machine learning, network analysis, and multimodal integration as major technical approaches. It focuses on the identification of metabolic abnormalities, the analysis of spatial heterogeneity, and the investigation of molecular mechanisms in major diseases, with the goal of developing interpretable, verifiable, and practically applicable methods for biomedical data analysis.