Fields of Research (FoR)Radiology and Imaging, Artificial Intelligence and Image Processing, Image Processing, Central Nervous System, Mental Health
Dr. Jiyang Jiang is a researcher in neuroimaging and brain ageing. He is currently appointed as a Postdoctoral Research Fellow at Centre for Healthy Brain Ageing (2016-). Dr. Jiang completed a PhD in Psychiatry degree from UNSW (2016). He also hold a Master of Professional Engineering (USYD, 2010) and a Bachelor of Engineering (2008) degrees. He has broad research interests in neuroimaging and ageing brains, including brain strucutral and...view more
Dr. Jiyang Jiang is a researcher in neuroimaging and brain ageing. He is currently appointed as a Postdoctoral Research Fellow at Centre for Healthy Brain Ageing (2016-). Dr. Jiang completed a PhD in Psychiatry degree from UNSW (2016). He also hold a Master of Professional Engineering (USYD, 2010) and a Bachelor of Engineering (2008) degrees. He has broad research interests in neuroimaging and ageing brains, including brain strucutral and functional changes in ageing, cerebrovascular imaging, imaging neuroinflammation, and application of machine learning in neuroimage segmentations and disease prediction.
- PhD in Psychiatry (UNSW, 2016)
- Master of Professional Engineering in Telecommunications (USYD, 2010)
- B.Eng in Mechtronics (BISTU China, 2008)
- 2020 Centre for Healthy Brain Ageing (CHeBA) Publication Award (Early Career category)
- 2019 Dementia Centre for Research Collaboration (DCRC) Travel Award
- 2015 Chinese Government Award for Outstanding Student Abroad, China Scholarship Council
My Research Activities
Full publication list on Google Scholar
Full publication list on Scopus
- Cerebrovascular lesions in ageing
- Lesion segmentations using machine learning techniques (convolutional neural network, recurrent neural network)
- Imaging biomarkers for vascular cognitive impairment and dementia
- Brain structural and functional changes in ageing
Contributions to Research Community
- I published a software package for neuroimaging data post-processing, called CHeBA Neuroimaging Software (CNS). It can be downloaded from here. One of the main modules is UBO Detector (see methodology paper) which is a machine learning-based, fully automated pipeline for the segmentation of white matter hyperintensities (WMH). TOolbox for Probabilistic MApping of Lesions (TOPMAL) is an extention of UBO Detector to map WMH lesions to strategic white matter fibre tracts to enable lesion symptom mapping studies (see TOPMAL paper).
Membership in Professional Organisations
- Member, Organization for Human Brain Mapping (2013-)
- Member, Society for Neuroscience (2016-)
- Member, International Society for Magnetic Resonance in Medicine (2017-)
- Member, Alzheimer's Association (2019-)
Editorship and Peer-reviewing
- Guest editor for the research topic 'Cerebrovascular Diseases and Neuropsychiatric Disorders in Ageing' for the journal Frontiers in Psychiatry.
- Peer-reviewer for a number of scientific journals, including Neuroimage, Human Brain Mapping, Neurobiology of Aging, Neuroimage Clinical, Journal of Gerontology: Biological Sciences, Journal of Neurological Sciences, etc.
- Member of abstract review team for 2019 Alzheimer's Association International Conference (AAIC), invited by the Scientific Program Committee's Neuroimaging workgroup.
My Research Supervision
Areas of supervision
- Structural and functional neuroimaging
- Brain ageing and dementias
- Application of machine learning techniques to medical image processing
- Imaging cerebrovascular system
- Abdullah Alqarni, PhD Student : Sex differences in white matter lesions
- Keshuo Lin, Honours Student : Automated rating of dilated perivascular space using machine learning techniques