Research title: Resource-aware & Adaptive Novelty Detection in Edge Computing Environments
Qiyuan wang received his Master’s degree in Data Science from the University of Glasgow(2020) and his Bachelor’s degree in Computer Science and Technology from China University of Mining and Technology(2019). He worked as a back-end developer intern in iQIYI and a data analyst intern in ADVANCE.AI.
His research focuses on outlier and novelty detection in Edge Computing environments. He seeks to investigate and contribute to this area by proposing new outlier detection models/frameworks that combine, modify and improve some outlier detection methods to adapt to the constraints in Edge Computing environments (reduce latency and computational complexity, decrease energy, memory and bandwidth consumption). Moreover, he expects to discover the latent relationship of the parameters of the parametric outlier detection methods with the detection effectiveness and provide formalised and systematic approaches to detect outliers in Edge Computing environments and generalise them to fit more application scenarios.
He will conduct his research in Essence: Pervasive & Distributed Computing Lab, IDA Section, School of Computing Science.