I am an Assistant Professor (Senior Lecturer) in Centre for Computational Science and Mathematical Modelling, Coventry University, UK. My current research interests are at the interface between control systems engineering and neuroscience - especially the use of nonlinear system identification to study complex nonlinear interactions in human brain network and diagnosis of neurological disorders (e.g. Alzheimer’s disease, tremor, seizures). I am also interested in statistical machine learnig, network inference and their applications in neuroscience and systems biology, e.g. identifying complex regulatory mechanisms in cellular (metabolic, genetic) networks.
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). I received a PhD and an MSc (distinction) in control engineering from 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, Proc. IEEE, Automatica, IET Systems Biology, Biophys. J., Int. J. Syst Science, Entropy). I am also the reviewer for international funding bodies (including EPSRC). Currently, I am a member of the UKRI Future Leaders Fellowships (FLF) peer review college.
If you are interested to apply for a postdoc Fellowship (e.g. Marie Sklodowska-Curie, UKRI, Leverhulme, Newton International) or a visiting position in my group, please do not hesitate to get in touch with me. Every year, I also have 1-2 fully-funded PhD studentship.
- Nonlinear system identification: NARMAX modelling & frequency-domain analysis
- Nonlinear connectivity, cross-frequncy coupling & causality analysis in neuroscience
- Network inference for complex biochemical and neurological networks
- Bayesian inference (parameter estimation and model selection), Gaussian Process, model-based experimental design
[Dec 2021] I am co-editing a Special issue for Frontiers in Computational Neuroscience & Frontiers in Neuroinformatics on Nonlinear Connectivity, Causality and Information Processing in Neuroscience. Welcome for submissions! Please submit your manuscript by 31 January, 2022.
[Oct 2021] I organised a CSM spotlight series event on Nonlinear connectivity and frequency-domain analysis in neuroscience, very pleased to invite Dr Alexander Zhigalov (Univ. of Birmingham) and my PhD student (Rajintha) to give joint seminar talks.
[Oct 2021] Fully-funded PhD studentships (international, UK/EU) are available for January 2022 start, jointly led by me and Dr Min Wu from Singapore A-STAR, on Network Inference, Brain Connectivity & Machine Learning. Application deadline: 04 October 2021. Please email me your CV before apply.
[August 2021] New preprint - D Klepl, F He, M Wu, DJ Blackburn, P Sarrigiannis, Bispectrum-based Cross-frequency Functional Connectivity: A Study of Alzheimer’s Disease, bioRxiv, doi: https://doi.org/10.1101/2021.08.07.455499, August 2021.
New preprint! Nice work from Dominik Klepl on Characterising Alzheimer’s Disease with EEG-based Energy Landscape Analysis. The results show AD patients’ brain network/state transition are more constrained with more local minima, less variation and smaller basins. Those features of Energy Landscape can potentially be used to predict AD with high accuracy.
Our review (with Dr Yuan Yang) on Nonlinear System Identification of Neural Systems from Neurophysiological Signals is published in Neuroscience. You can find the preprint here.