Defence of doctoral thesis in the field of Biomedical Engineering, MSc Ivan Zubarev

Title of the doctoral thesis is "Developing machine-learning methods for the analysis of electromagnetic brain activity"

This thesis summarizes how machine-learning methods can be used to decode non-invasive measures of the human brain activity measured with electro- (EEG) and magnetoencephalography (MEG), with a particular focus on how the patterns that these methods extract from the data can be interpreted in a way that advances our understanding of the functioning of the human brain. The methods developed in this thesis can be applied in brain research, development of brain computer-interfaces, as well as identifying functional biomarkers of various neurological conditions.

Opponent: Professor Surjo Soekadar, Charité –University Medicine Berlin, Germany

Custos: Professor Lauri Parkkonen, Aalto University School of Science, Department of Neuroscience and Biomedical Engineering

Doctoral candidate's contact information: [email protected], +358505121760

The defence will be organized via remote connection (Zoom). Link to the defence 

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The doctoral thesis will be publicly displayed 10 days before the defence in the publication archive of Aalto University.

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