Academic Staff

Our goal is to develop core technologies for generating new value and knowledge from sensor information derived from multiple observations. An important application domain is intelligent manufacturing, where advanced data analysis and machine learning techniques are required to estimate the behaviour of complex and diverse human activities, such as the assembly behaviour of workers in manufacturing silos. We are also working on various time-series data processing technologies, such as concise data management, forecasting and anomaly detection from massive data in the natural sciences, such as astronomy and meteorology.