Steven Golovkine is a post-doctoral researcher in Statistics and Data Analysis in the Department of Mathematics and Statistics at the University of Limerick working on the SFI Functional data Analysis for Sensor Technologies (FAST) project.


His current research interest focuses on the development of novel, computationally efficient statistical models and algorithms for the modeling of multivariate sensor data. Examples of application include functional magnetic resonance imaging (fMRI), accelerometer data in sport science, electrocardiogram (ECG) monitors in cardiology and IoT for e-health. This work is supervised by Norma Bargary (UL) and Andrew Simpkin (NUI Galway) and funded by the Insight
SFI Research Centre for Data Analytics.


He received both his M.S. in Statistics (Diplôme d’ingénieur, 2017) and his MSc in Big Data (2017) from the National School for Statistics and Data Analysis (ENSAI), France. He holds a PhD in Mathematics and their interactions from ENSAI, France in collaboration with Groupe Renault on the topic "Statistical methods for multivariate functional data. 

 

Research Interests: Functional Data Analysis, Clustering, Non-Parametric Statistics, Sport Data Analytics, Machine Learning. 

Working with: Prof. Norma Bargary