• Lecturer (higher education)
• Gender:Male
• Date of Birth:1987-04-06
• Alma Mater:The University of Tokyo
• Education Level:博士研究生
• Degree:Doctoral Degree in Engineering
• Date of Employment:2017-09-19
• School/Department:华侨大学信息学院
• Business Address:华侨大学厦门校区机电信息大楼B544
• E-Mail:14e9168b9f50e6e5f73a8a5ade2bbdf5ae2ac5c3de99025c178e35bbbfafc5f8921633cc182131d73526175476ebe8375ff269665f7672ee6b9bc9177113020b6fe92e9915642ea58982dab6980f043706e77d89748d951d05d60ea5b5fdef5754c7433b135b8ce1ba35c6f8ff14b3870261fc2039ce903ca8bb142880220669
• Status:在岗
• Administrative Position:讲师
• Discipline:Pattern Recognition and Intelligent Systems
  Signal and Information Processing
  Biomedical Engineering
  Biomedical Engineering
  

2023-09-30   厦门市高层次人才B类

2023-09-30   福建省高层次人才B类

2022-09-30   厦门市高层次人才C类

2022-09-30   福建省高层次人才C类

2019-04-30   泉州市人才

2018   福建省引进高层次人才

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Dr. Fang Duan is a Lecturer at the College of Information Science and Engineering, Huaqiao University. His research focuses on biomedical signal processing and brain network computing, covering EEG/ERP and MEG signal analysis, brain network modeling and developmental analysis, neural decoding and brain-computer interfaces, as well as non-invasive neuromodulation for clinical rehabilitation applications. He received his B.E. degree in Automation from Zhejiang University in 2006, his M.S. degree in Biomedical Engineering from Tsinghua University in 2011, and his Ph.D. degree in Electrical Engineering from The University of Tokyo in 2014, where he was supported by a MEXT (Ministry of Education, Culture, Sports, Science and Technology of Japan) scholarship and worked under the supervision of Prof. Kazuyuki Aihara, collaborating with the Research Center for Child Mental Development of Kanazawa University on pediatric MEG studies. He was a Research Fellow at the Institute of Industrial Science, The University of Tokyo, from 2014 to 2018, where he participated in EEG data analysis research on schizophrenia. He joined Huaqiao University in September 2017. His current research includes neural feature extraction and fusion (e.g., event-related potentials and phase-amplitude coupling) for EEG decoding with domain-shift characterization and adaptive generalization across subjects and devices, with applications to sleep health monitoring and cognitive assessment; brain network modeling using complex network and graph-theoretic methods, including subnetwork development patterns in children with autism spectrum disorder via non-negative matrix factorization, MEG-based brain network and cognitive performance in children, and preictal epileptogenic network dynamics in drug-resistant epilepsy based on stereoelectroencephalography (SEEG); and prospective studies on non-invasive neuromodulation such as transcutaneous vagus nerve stimulation (tVNS) for epileptic encephalopathy. He has published papers in journals including Biomedical Signal Processing and Control, Computers in Biology and Medicine, Journal of Child Neurology, Brain Sciences, PLOS ONE, and Brain and Cognition.