Photo of Fei He

Fei He


    Accepting PhD Students

    • Source: Scopus
    • Calculated based on no. of publications stored in Pure and citations from Scopus

    Research output per year

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    Personal profile


    I joined Coventry University as a Senior Lecturer in Data Science in 2018. Before joining Coventry, I previously held research positions at Imperial College London (Theoretical Systems Biology group), University of Sheffield, and University of Manchester (Manchester Centre for Integrative Systems Biology). My research has focused on developing statistical machine learning and control systems engineering approaches to study the complex regulatory mechanisms in cellular (metabolic, genetic) networks, as well as complex nonlinear interactions in human brain network that relate to neurological disorders/diseases (e.g. Alzheimer’s disease, seizures).

    I received a PhD and an MSc (distinction) in control engineering from the University of Manchester. I am editorial board member of Frontiers in Computational Neuroscience, and have served as reviewer for a number of peer-reviewed journals (including 4 IEEE Transactions, Proceedings of IEEE, Automatica, IET Systems Biology, Biophysical Journal, Int. J. Syst Science, Entropy). I am also the reviewer for international funding bodies (including EPSRC).


    • Module leader - 7037CEM, Machine Learning
    • Module leader - 7089CEM, Introduction to Statistical Methods for Data Science
    • Lecturer - 230MP Advanced Matlab: Data Science and ML
    • Supervisor - 300COM Final year project, M08CDE MSc project
    • Module leader - CPE6005/CPE422 Bio-systems Engineering and Computational Biology, 2015 - 2017, University of Sheffield.

    Research Interests

    Computational Neuroscience - Nonlinear systems identification, Signal processing and Causality analysis

    • NARMAX model-based nonlinear frequency analysis & causality analysis
    • Nonlinear time-frequency modelling and diagnosis of neurological disorders (e.g. seizures, Alzheimer’s disease) based on neurophysiological recordings: EEG, EMG, fMRI

    Computational Systems Biology

    • Bayesian inference for parameter estimation and model selection
    • Optimal and Bayesian model-based experimental design
    • Network inference for complex biochemical regulatory pathways

    PhD Project

    If you are interested to do a PhD in statistical machine learning, Bayesian inference, nonlinear signal processing/system identification with possible applications in biology or neuroscience, please get in touch with me

    • I have fully-funded PhD studentships (long-term effective) jointly with Singapore A*STAR on network inference & computational biology/neuroscience. For Jan 2021 entry, see the FindaPhD link for details. The applicaiton for Sep 2021 entry will open on early 2021.



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