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Congratulations for Miao Sun

PhD defense - 15 June 2022

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New NWO project: GRASPA

Six research projects receive funding within the Open Technology Programme (OTP) this month. The projects receive a total of about 4 million euros from NWO; organisations involved in the research projects invest a total of 1.3 million euros. Among these 6 projects is a project from prof. Geert Leus from the CAS group; Graph Signal Processing in Action (GraSPA).

Graph signal processing (GSP) is the exciting research field that extends concepts from traditional signal processing to signals living in an irregular domain that can be characterized through a graph. GSP is extremely promising for applications in transportation networks, smart grid, wireless communications, social networks, brain science and recommender systems, to name a few. This project focuses on the non-trivial extension of GSP to time-varying or dynamic networks, where either the connections or the nodes can change. We will develop innovative tools to estimate such time-varying graphs from data and devise new graph filtering schemes for denoising, interpolation, and prediction. The developed techniques will be applied to brain activity monitoring, which is crucial to understand the working of the brain, as well as recommender systems, which are omnipresent in our daily lives.

More information: Four million euro for six technological research projects | NWO

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New NWO-TTW project: GraSPA

Graph signal processing (GSP) is the exciting research field that extends concepts from traditional signal processing to signals living in an irregular domain that can be characterized through a graph. GSP is extremely promising for applications in transportation networks, smart grid, wireless communications, social networks, brain science and recommender systems, to name a few. This project focuses on the non-trivial extension of GSP to time-varying or dynamic networks, where either the connections or the nodes can change. We will develop innovative tools to estimate such time-varying graphs from data and devise new graph filtering schemes for denoising, interpolation, and prediction. The developed techniques will be applied to brain activity monitoring, which is crucial to understand the working of the brain, as well as recommender systems, which are omnipresent in our daily lives.

This project will fund 2 PhD students. PIs are Geert Leus and Elvin Isufi.

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