(DAVID) DAGAN FENG
ME SJTU, MSc UCLA, PhD UCLA,
Professor, FACS, FHKIE, FIEEE, FIET, and FTSE
School of Information Technologies
Professor (David) Dagan Feng is a respected authority on biomedical information and multimedia information technology. He has led more than 50 national and international research projects. In conjunction with his collaborators, he has published over 860 scholarly research papers, pioneered several new research directions, and made a number of landmark contributions in his field. He has served as Chair of the International Federation of Automatic Control (IFAC) Technical Committee on Biological and Medical Systems, and Special Area Editor / Associate Editor for a dozen of key journals in his area, as well as Deputy Chair of Health and Technology Forum, Australian Academy of Technological Sciences and Engineering. He has been invited to give over 100 keynote presentations in 23 countries and regions, and has organized / chaired over 100 major international conferences / symposia / workshops. He is the Founding Director, Institute of Biomedical Engineering & Technology, and Academic Director, USYD-SJTU Joint Research Alliance, at the University of Sydney.
Research Highlight 1
Biomedical Information Technology is an emerging area to deal with developing bio-inspired new technologies for information processing, as well as novel applications of information technology to complex biomedical systems.
Developed a set of new theories in this area, from data acquisition, storage, management, processing, analysis and modeling, such as developed optimal image sampling schedule, diagnose lossless data compression, medical feature based medical image retrieval, and medical knowledge-based intelligent image processing, etc. Edited the world’s first research book “Biomedical Information Technology” published by Elsevier, Academic Press in 2008. The second edition is expected to appear in 2019.
Research Highlight 2
Functional imaging (such as position emission tomography – PET) – is an indispensible technique to unravel the complex biological systems in the living human body and quantify the biomedical functions at the cellular level.
Pioneered a set of theories for functional imaging quantification, as well as applied to clinical studies: such as Feng-IF (input function) approach for non-invasive quantification and GLLS (Generalised linear least square) parametric imaging techniques. They have been used in studying the local cerebral / myocardium blood flow and metabolic rate of glucose, and early detection of liver (HCC) cancer.
Research Highlight 3
Biomedical system modeling can greatly improve the understanding of the complex biological and medical systems both qualitatively and quantitatively.
Developed a number of theories, including a graph theory based approach for compartmental modelling that was able to generate mathematical descriptions, in which the required equivalence transformations are easily performed, facilitating the discovery of thyroid hormone conversion rates and protein synthesis rates.
Research Highlight 4
Multimedia computing and data fusion are the core areas for big data analytics, where all of the related data and information can be integrated and processed / analysed together.
Developed a number of techniques for multimedia information retrieval and management, various approaches for multidimensional and multimodality image registration, image segmentation and image analysis, with applications in a broad range of different areas, as well as edited the book “Multimedia Information Retrieval and Management published be Springer in 2003.