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Weikang Gong

Postdoctoral Researcher

Research Summary

I am a postdoctoral researcher in the FMRIB Analysis Group, which is part of the Wellcome Centre for Integrative Neuroimaging and Nuffield Department of Clinical Neurosciences. I am currently working with Professor Stephen Smith and Professor Christian Beckmann. My research interest is in the area of statistical modelling of brain image and genetics data, especially the multimodal data fusion using big datasets such as Human Connectome Project and UK-Biobank.

Our work, BigFLICA, on a new multimodal fusion algorithm for large-scale neuroimaging dataset is out in Medical Image Analysis. We have improved this work by an end-to-end supervised training algorithm called SuperBigFLICA, now the preprint is out in BioRxiv.

Our work on a new deep learning model for brain age prediction using UKB data is out in Medical Image Analysis

Besides methodology research, I also have core contributions to several of our neuroscientific research projects: Our work on the associations of family environment with the brain and behaviours is out in Nature Communications. Our work on the relations between sleep durations, brain and behaviours is out in Molecular Psychiatry. Our work on the relations between parental age, brain and behaviours is out in Molecular Psychiatry.

I obtained my DPhil degree from FMRIB, WIN, NDCN at Oxford. Before joining the DPhil programme, I obtained a MSc degree in Computational Biology from SIBS in Chinese Academy of Sciences, collaborated with ISTBI at Fudan University. I did my undergraduate in Mathematics at Shandong University. My previous work developed approaches to perform voxel-level functional connectivity analysis using resting-state fMRI. The approaches called BWAS is published in Medical Image Analysis, and sKPCR published in NeuroImage. I also wrote a Matlab-based software package to preprocess the resting-state fMRI data. 

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