Sepehr Maleki is a Research Fellow in College of Science working on a joint project with Siemens. Applying machine learning and statistical techniques on the ``Big Data’‘, collected from the fleet of Siemens gas turbines all around the globe, his research focuses on developing an assistive tool that helps detection and classification of a failure upon occurrence in the network.
Prior to this he was a postgraduate researcher at the University of Southampton. His research focused on developing a model-based approach to address the Fault Detection and Isolation (FDI) problem in multidimensional systems.
Fault Detection and Isolation, Changepoint Detection, Multidimensional Systems, Machine Learning, Gaussian Processes