The Audio Engineering Society (AES), the IEEE Consumer Technology Society (CTSoc), and the IEEE Signal Processing Society (SPS) cordially invite you to a first-of-a-kind joint event discussing the state of the art perspectives in this rapidly evolving field.

Shrikanth (Shri) Narayanan is University Professor and Niki & C. L. Max Nikias Chair in Engineering at the University of Southern California, where he is Professor of Electrical & Computer Engineering, Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head & Neck Surgery, Director of the Ming Hsieh Institute and Research Director of the Information Sciences Institute. 

This dissertation develops Defense through AI-powered SYstem-scientific methods (DAISY) for high-confidence Cyber-Physical Systems (CPSs).  We start by designating five generations of Security Paradigms (SPs) that have evolved since the birth of the Internet.

The IEEE Signal Processing Society is excited to announce we are partnering with the IEEE Humanitarian Activities Committee (HAC) to conduct a special Call for Proposals to support projects in SPS chapters that utilize Signal Processing technologies to address local community challenges.

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.

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 Principal Component Analysis (PCA) is considered to be a quintessential data preprocessing tool in many machine learning applications. But the high dimensionality and massive scale of data in several of these applications means the traditional centralized PCA solutions are fast becoming irrelevant for them. 

Privacy issues and communication costs are both major concerns in distributed optimization in networks. There is often a tradeoff between them because encryption methods used for privacy-preservation often introduce significant communication overhead.

In past decades, conventional communication primarily focused on how to accurately and effectively transmit symbols, which is categorized as the first level of communications by Shannon and Weaver. With the developments of cellular communication systems, the achieved transmission rate is gradually approaching to the Shannon limit.