Graphs are generic models of signal structure that can help to learn in several practical problems. To learn from graph data, we need scalable architectures that can be trained on moderate dataset sizes and that can be implemented in a distributed manner. Drawing from graph signal processing, the webinar will define graph convolutions and use them to introduce graph neural networks (GNNs). 

Join us in the second year of PROmotinG DiveRsity in Signal ProcESSing (PROGRESS), which is an initiative of the IEEE Signal Processing Society designed to motivate, provide information and support women and under-represented minorities in pursuing academic careers in signal processing. 

This thesis addresses security and privacy problems for digital devices and biometrics, where a secret key is generated for authentication, identification, or secure computa- tions. A physical unclonable function (PUF) is a promising solution for local security in digital devices.

IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

The IEEE Signal Processing Society has developed guidelines related to SPS Chapter social media and Chapter Activities.