• Qi (Roger) SHE

    Ph.D. Candidate, City University of Hong Kong


    I am a Computational Neuroscience Ph.D. candidate at City University of Hong Kong where I am advised by Dr. Rosa H.M. Chan. My research focuses on statistical machine learning methods to extract hidden structure from high-dimensional spike-train data, infer brain connectivity using fully & empirical bayes, and complex network study on multiple brain regions. I am interested in studying how information is encoded, decoded, and processed our brain. I completed my B.Eng. within 2% in Optical and Electronic Engineering at Nanjing University of Posts and Telecommunications in September 2014.

  • Publications

    1. Qi She, Beth Jelfs, Rosa H.M. Chan, "Modeling Short Over-Dispersed Spike-Train Data: A Hierarchical Parametric Empirical Bayes Framework", arXiv:1605.02869 [q-bio.QM]
    2. Ka Yan So, Lingling Yang, Qi She, Wai Ho Savio Wong, Joe Mak, Rosa H. M. Chan "Cross-Frequency Information Transfer from EEG to EMG in Grasping, "Proceedings of Annual International Conference of the IEEE EMBS, 2016, accecpted.
    3. Qi She, Ka Yan So, and Rosa H. M. Chan"Effective Connectivity Matrix for Neural Ensembles,"Proceedings of Annual International Conference of the IEEE EMBS, 2016, accecpted.
    4. Qi She, Guanrong Chen, and Rosa H. M. Chan"Evaluating the Small-World-Ness of a Sampled Network: Functional Connectivity of Entorhinal-Hippocampal Circuitry," Scientific Reports 6, 2016
    5. Qi She, Ka Yan So, and Rosa H. M. Chan"Reconstruction of Neural Network Topology Using Spike Train Data: Small-World Features of Hippocampal Network,"Proceedings of Annual International Conference of the IEEE EMBS, pp 2506-2509, 2015.(Oral presentation)
    6. X Hu, S Chakravarty, Q She, B Wang" A modified hierarchical graph cut based video segmentation approach for high frame rate video," IS&T/SPIE Electronic Imaging, 86610V-86610V-11,2013