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Dr Kongfatt Wong-Lin Lecturer

School of Computing & Intelligent Sys
Research Institute
Computer Science
Room MS136
Magee campus
BT48 7JL

+44 (0)28 716 75320
Kongfatt   Wong-Lin

KongFatt Wong-Lin is a Lecturer at the School of Computing and Intelligent Systems. He has led the Computational Neuroscience Research Team at the Intelligent Systems Research Centre at Magee campus. Previously, he was a research associate at the Program in Applied and Computational Mathematics, Princeton University, USA, in mathematical and cognitive neurosciences, with affiliation to Princeton Neuroscience Institute. Prior to that, he received his Ph.D. in Physics with focus on Computational Neuroscience at Brandeis University, USA, with affiliation to the Volen National Center for Complex Systems. Dr. Wong-Lin's research interest is in computational modelling and analysis of systems and cognitive neuroscience, and more recently on computational neuroimaging, brain disorders and mental health, and data analytics. He often works on the interface of biology, psychology, computing and mathematics. He has published his research works in leading journals across several fields, and his computational models used by several forefront research groups, including the Virtual Brain software. His computational modelling work has received the Best Paper Award at the IJCNN 2011 international conference. He is also a guest editor for Frontiers in Integrative Neuroscience. Reflecting his multidisciplinary research approach, he is a member of several professional societies, including Society for Neuroscience, British Neuroscience Association, Society for Mathematical Biology, and IEEE. Dr. Wong-Lin has mentored several postdoctoral researchers, and Ph.D. and Masters students working on computational neuroscience and related research areas. He has received multiple research grants to support various neuroscience and neuro-inspired projects.

Research publications

Showing 1 to 5 of 78 publications
To view all publications please visit Ulster University Institutional Repository (UIR)