SungJun Cho
BS/BA, MSc
DPhil Student
Research Interests
I am a first-year DPhil student in the OHBA Analysis Group at the University of Oxford, advised by Mark Woolrich and Oiwi Parker Jones. My research focuses on the development of new statistical and machine learning methods for analysing M/EEG data and their application to various neuropsychiatric disorders. I am generously supported by the Medical Sciences Graduate School studentship, funded by the MRC, NDCN, and Hertford College.
Previously, I received an MSc (by Research) in Psychiatry from the same group. During my master's, I studied dynamic resting state networks of MEG and EEG in healthy ageing and early Alzheimer's disease. I completed my undergraduate studies in neuroscience and philosophy at the University of Chicago.
Recent publications
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Comparison between EEG and MEG of static and dynamic resting-state networks.
Journal article
Cho S. et al, (2024), Hum Brain Mapp, 45
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Mouse Escape Behaviors and mPFC-BLA Activity Dataset: Understanding Flexible Defensive Strategies Under Threat.
Journal article
Cho S. et al, (2024), Sci Data, 11
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Comparison between EEG and MEG of static and dynamic resting-state networks
Preprint
Cho S. et al, (2024)
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A guide towards optimal detection of transient oscillatory bursts with unknown parameters.
Journal article
Cho S. and Choi JH., (2023), J Neural Eng, 20
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Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning
Conference paper
Lee H. et al, (2023), 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2308 - 2317