The coronavirus (COVID-19) pandemic has led to widespread morbidity and mortality. Several countries have been forced into prolonged lockdowns in a desperate attempt to control the pandemic by physical distancing. Such lockdowns have devastated livelihoods and put large numbers of people at grave risk of prolonged unemployment, poverty, and even starvation.

Dr. Yonina Eldar is a Professor in the Department of Mathematics and Computer Science, Weizmann Institute of Science, Rechovot, Israel. She was previously a Professor in the Department of Electrical Engineering at the Technion, where she held the Edwards Chair in Engineering.

Given the impossibility of travel during the COVID-19 crisis,  Computational Imaging TC is launching an SPS Webinar Series SPACE (Signal Processing And Computational imagE formation) as a regular bi-weekly online seminar series to reach out to the global computational imaging and signal processing community.

Deep neural networks achieve state-of-the-art performance in many domains in signal processing. The main practice is getting pairs of examples, input, and its desired output, and then training a network to produce the same outputs with the goal that it will learn how to generalize also to new unseen data, which is indeed  the case in many scenarios.

This issue brings to you our interview with Dr. Maryam Azimi, an active IEEE Signal Processing Society (SPS) Young Professional. 

July and August usually represent months of relaxation and vacations. These are the months that typically would not see too many exciting things going on in the signal processing community. Occasional cool papers here and there would be the only exciting things happening in July and August. 

In 2000, compact discs were the dominant mode of music distribution and the use of digital compressed audio files for playback using computers was just beginning. Most of the research on analyzing music was done with symbolic representations rather than audio signals. The presenter, Dr. George Tzanetakis, is fascinated by pattern recognition, computer vision, and speech recognition. 

As a reminder, most of the SPS publications have eliminated month-based issues and moved to a volume-only, continuous pagination model. This allows for rapid dissemination of content for our journals and now, articles are posted to their respective journals on IEEEXplore® nearly every day! 

The Signal Processing Society (SPS) has 13 Technical Committees and 2 Special Interest Groups (SIGs) that support a broad selection of signal processing-related activities defined by the scope of the Society.