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Shile Qi

  • Post-Doctoral Research Fellow
  • Ph.D, Medical Imaging Analysis from Institute of Automation, Chinese Academy of Sciences, China
  • MS, Mathematics, Fuzhou University, China
  • B.S., Mathematics, Zhoukou University, China
  • sqi@mrn.org
  • I work as a postdoc for The Mind Research Network under Dr. Vince Calhoun. My research interests include multimodal brain imaging fusion, developing novel algorithms for fusion, and individualized prediction. I received B.S. degree in Mathematics from Zhoukou Normal University (Zhoukou, China), and received M.S in Mathematics from Fuzhou University, (Fuzhou, China) and Ph.D degree in Medical Imaging Analysis from Institute of Automation, Chinese Academy of Sciences, (Beijing, China). My current projects focus on supervised fusion analysis for multimodal brain imaging data. The supervised fusion is a goal-directed model that employs prior information as a reference to guide multimodal data fusion which can precisely identify co-varying multimodal imaging patterns closely related to the reference, such as cognitive scores, medication use and behavioral measures (e.g., temperament inventory), or even epigenetic variants (e.g., a microRNA expression).