Samsung Advanced Institute for Health Sciences and Technology (SAIHST) - Samsung Advanced Institute for Health Sciences and Technology (SAIHST)

  • Assistant Professor
  • YOO, KWANG SUN 홈페이지 바로가기

Education

  • (Ph.D.) 2015. Bio and Brain Engineering, KAIST.

Experience

  • 2017 - 2021. Post-doc, Yale University, USA.
  • 2021 - 2023. Associate Research Scientist (Research Faculty), Yale University, USA.
  • 2023 - present. Assistant Professor, Department of Digital Health, SAIHST, Sungkyunkwan University
  • 2023 - present. Assistant Professor, Data Science Research Institute, Research Institute for Future Medicine, Samsung Medical Center

Journal Articles

  • (2024)  Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention.  JOURNAL OF NEUROSCIENCE.  44,  14
  • (2023)  Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank.  LANCET DIGITAL HEALTH.  5,  6
  • (2022)  Differences in the functional brain architecture of sustained attention and working memory in youth and adults.  PLOS BIOLOGY.  20,  12
  • (2022)  A cognitive state transformation model for task-general and task-specific subsystems of the brain connectome.  NEUROIMAGE.  257, 
  • (2022)  A brain-based general measure of attention.  NATURE HUMAN BEHAVIOUR.  6, 
  • (2022)  Antagonistic network signature of motor function in Parkinson's disease revealed by connectome-based predictive modeling.  NPJ PARKINSONS DISEASE.  8, 
  • (2021)  Predicting multilingual effects on executive function and individual connectomes in children: An ABCD study.  PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA.  118,  49
  • (2019)  Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors.  NEUROIMAGE.  197, 
  • (2018)  Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.  NEUROIMAGE.  167, 
  • (2017)  Degree-based statistic and center persistency for brain connectivity analysis.  HUMAN BRAIN MAPPING.  38,  1