Research output per year
Research output per year
Personal profile
Research Interests
Network neuroscience - signal processing - machine learning - graph inference
- Functional connectivity models
- Graph classification and embedding
- Graph neural network
Master's Project
Energy landscape of Alzheimer's disease EEG - prediction
PhD Project
Network Inference And Machine Learning: Identification Of Neurodegenerative Diseases
Education/Academic qualification
Data science and computational intelligence, MSc, Coventry University
15 Sep 2019 → 11 Sep 2020
Award Date: 11 Sep 2020
Cognitive Science, Degree, Aarhus University
1 Sep 2016 → 30 May 2019
Award Date: 30 May 2019
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Bispectrum-based Cross-frequency Functional Connectivity: A Study of Alzheimer’s Disease
Klepl, D., He, F., Wu, M., Blackburn, D. J. & Sarrigiannis, P. G., 8 Aug 2021, bioRxiv, 9 p.Research output: Working paper › Preprint
Open AccessFile4 Downloads (Pure) -
Characterising Alzheimers Disease with EEG-based Energy Landscape Analysis
Klepl, D., He, F., Wu, M., De Marco, M., Blackburn, D. & Sarrigiannis, P. G., 18 Aug 2021, (E-pub ahead of print) In: IEEE Journal of Biomedical and Health Informatics. (In-press), p. (In-press)Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Downloads (Pure)