SERAM - Supporting users in exploring and reasoning about anomalies in multivariate timeseries

Project: Research project

Project Details


The overall goal of the project is providing data- and visual analytics methods for an effective Human-AI collaboration in decision making processes. In this subproject, we will put a particular focus on providing an AI system which helps human users to readily identify, explore and reason about anomalies in multivariate time series data. Within this context, the AI will be responsible for the anomaly candidate detection, and the human users by optimizing the entire AI process, by using techniques for annotation, active learning etc.
Effective start/end date1/07/2131/03/23


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