Learning dynamics from heterogeneous industrial time series data

Enormous amounts of industrial time series data are gathered all the time from sensors in the process industry. In my PhD project, I investigate how these data can be exploited despite the fact that they in many cases are noisy, incomplete and irregularly sampled in time.