Prof. Rihui LI

  • 2020 PhD., Biomedical Engineering, University of Houston, Houston, TX, USA
  • 2015 M.S., Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
  • 2012 B.S., Biomedical Engineering, Sun Yat-sen University, Guangzhou, China

  • 07/2020 – 02/2023 Postdoctoral Research Fellow, Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA

  • 2015-2020 Graduate Tuition Fellowship, University of Houston
  • 2015, 2016 Presidential Fellowship, University of Houston
  • 2014, 2015 Outstanding Graduate Student, Sun Yat-sen University
  • 2014 First prize of the 12th Guangdong “Challenge Cup” science and technology competition

My research aims to enhance our knowledge of the neural processes behind typical and atypical human behaviors through a combination of multimodal brain imaging techniques and computational methods. Specifically, my research interests include the following:

  • Development of integrated multimodal brain imaging algorithms (fNIRS, DOT, EEG, fMRI) for advanced brain imaging with high spatiotemporal resolution
  • Static and dynamic human brain network analyses to decode the process of human behaviors (Social interaction, team collaboration)
  • Establish computational models to elucidate the brain-physiology-behavior association of human brain disorders (neuropsychiatric, neurodegenerative and neurodevelopmental disorders)

  • 2021-2023 Project of “Uncovering Neurobiological Signatures of Social Interaction Dysfunction in Children with Fragile X Syndrome” Supported by The Maternal & Child Health Research Institute at Stanford University

  • Professional service
    • Associate editor, Frontiers in Clinical Engineering
    • Guest Associate Editor, Frontiers in Neuroscience
    • Guest Associate Editor, Frontiers in Behavioral Neuroscience
    • Ad-hoc Reviewers for Cerebral Cortex, Journal of Neural Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Journal of Biomedical and Health Informatics, IEEE Access, Frontiers in Human Neuroscience, Frontiers in Neuroscience, Frontiers in Psychology, etc.
  • Professional Societies
    • Member, the Society for Functional Near-infrared Spectroscopy
    • Member, the Society for Neuroscience

  • CCBS7005 Computational Cognitive Neuroscience
  • ECEN7021 Biomedical Transducers and Instruments

  • Liu J, Sun L, Huang M, Xu Y, Li R*: Enhancing Emotion Recognition Using Region-Specific Electroencephalogram Data and Dynamic Functional Connectivity. Frontiers in Neuroscience 2022:
  • Li R, Yang D, Fang F, Hong K-S, Reiss AL, Zhang Y: Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review. Sensors 2022, 22:
  • Li R, Bruno JL, Lee CH, Bartholomay KL, Sundstrom J, Piccirilli A, Jordan T, Miller JG, Lightbody AA, Reiss AL: Aberrant brain network and eye gaze patterns during natural social interaction predict multi-domain social-cognitive behaviors in girls with fragile X syndrome. Molecular Psychiatry 2022:1-9.
  • Li R, Mayseless N, Balters S, Reiss AL: Dynamic inter-brain synchrony in real-life inter-personal cooperation: A functional near-infrared spectroscopy hyperscanning study. NeuroImage 2021, 238:
  • Li R, Bruno JL, Jordan T, Miller JG, Lee CH, Bartholomay KL, Marzelli MJ, Piccirilli A, Lightbody AA, Reiss AL: Aberrant Neural Response During Face Processing in Girls With Fragile X Syndrome: Defining Potential Brain Biomarkers for Treatment Studies. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
  • Balters S†, Li R†, Espil FM, Piccirilli A, Liu N, Gundran A, Carrion VG, Weems CF, Cohen JA, Reiss AL: Functional near-infrared spectroscopy brain imaging predicts symptom severity in youth exposed to traumatic stress. Journal of psychiatric research 2021, 144:494-502.
  • Li R, Zhao C, Wang C, Wang J, Zhang Y: Enhancing fNIRS analysis using EEG rhythmic signatures: an EEG-informed fNIRS analysis study. IEEE Transactions on Biomedical Engineering 2020, 67:2789-2797.
  • Li R, Li S, Roh J, Wang C, Zhang Y: Multimodal neuroimaging using concurrent EEG/fNIRS for poststroke recovery assessment: an exploratory study. Neurorehabilitation and Neural Repair 2020, 34:1099-1110.
  • Cicalese PA†, Li R†, Ahmadi MB, Wang C, Francis JT, Selvaraj S, Schulz PE, Zhang Y: An EEG-fNIRS hybridization technique in the four-class classification of alzheimer’s disease. Journal of neuroscience methods 2020, 336:
  • Li R, Rui G, Zhao C, Wang C, Fang F, Zhang Y: Functional network alterations in patients with amnestic mild cognitive impairment characterized using functional near-infrared spectroscopy. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2019, 28:123-132.
  • Li R, Potter T, Wang J, Shi Z, Wang C, Yang L, Chan R, Zhang Y: Cortical hemodynamic response and connectivity modulated by sub-threshold high-frequency repetitive transcranial magnetic stimulation. Frontiers in Human Neuroscience 2019, 13:
  • Li R, Nguyen T, Potter T, Zhang Y: Dynamic cortical connectivity alterations associated with Alzheimer’s disease: An EEG and fNIRS integration study. NeuroImage: Clinical 2019, 21:
  • Li R, Rui G, Chen W, Li S, Schulz PE, Zhang Y: Early detection of Alzheimer’s disease using non-invasive near-infrared spectroscopy. Frontiers in aging neuroscience 2018, 10:
  • Li R, Potter T, Huang W, Zhang Y: Enhancing performance of a hybrid EEG-fNIRS system using channel selection and early temporal features. Frontiers in human neuroscience 2017, 11: