Time Series Analysis
time series analysis
Felipe Tobar
The Initiative for Data & Artificial Intelligence at Universidad de Chile is looking for Postdoctoral Researchers to join a collaborative team of PIs working on theoretical and applied aspects of Data Science. The role of the postholder(s) is twofold: first, they will engage and collaborate in current projects at the Initiative related to statistical machine learning, natural language processing and deep learning, with applications to time series analysis, health informatics, and astroinformatics. Second, they are expected to bring novel research lines affine to those currently featured at the Initiative, possibly in the form of theoretical work or applications to real-world problems of general interest. These positions are offered on a fixed term basis for up to one year with a possibility for a further year extension.
Localisation of Seizure Onset Zone in Epilepsy Using Time Series Analysis of Intracranial Data
There are over 30 million people with drug-resistant epilepsy worldwide. When neuroimaging and non-invasive neural recordings fail to localise seizure onset zones (SOZ), intracranial recordings become the best chance for localisation and seizure-freedom in those patients. However, intracranial neural activities remain hard to visually discriminate across recording channels, which limits the success of intracranial visual investigations. In this presentation, I present methods which quantify intracranial neural time series and combine them with explainable machine learning algorithms to localise the SOZ in the epileptic brain. I present the potentials and limitations of our methods in the localisation of SOZ in epilepsy providing insights for future research in this area.
Performing highly comparative time series analysis of local field potentials during anaesthesia and wakefulness
Neuromatch 5