Inuk Song
Graduate Student Researcher
Blacksburg, Virginia, United States
Summary
👤
Senior🎓
Top SchoolInuk Song is a graduate student researcher in biological psychology at Virginia Tech with eight years of experience combining EEG, fMRI, and machine learning to probe cognition and physiology. His work spans deception detection with EEG, cybersickness mitigation using brain stimulation, and comparative studies of real versus virtual memory retrieval, and he now focuses on dynamic resting-state fMRI, locus coeruleus connectivity, and graph-theoretic functional connectivity methods. He brings practical skills in multimodal data processing (simultaneous EEG-fMRI), artifact reduction, and ML classification of dynamic connectivity, and has translated psychophysiological insights into novel analytic tools. Based in Blacksburg, VA, he blends deep experimental neuroscience training from Korea University with growing computational expertise at Virginia Tech, uniquely positioning him to bridge neural measurement and scalable analytic methods.
8 years of coding experience
5 years of employment as a software developer
Graduate Student, Biological Psychology, Graduate Student, Biological Psychology at Virginia TechMaster of Science - MS, Behavioral and Cognitive Neuroscience, Master of Science - MS, Behavioral and Cognitive Neuroscience at Korea University
Stackoverflow
1reputation
0reached
0answers
0questions
Github contributions (5)
Psyence221b/EssentialEEGAnalysis
Oct 2018 - Feb 2020
Contributions:11 commits, 22 pushes, 1 branch in 1 year 4 months
Psyence221b/Psyence221b.github.io
Feb 2019 - Feb 2019
"Best Jekyll Theme by a Mile"
Contributions:21 pushes in 1 day
jekylljekyll-theme
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