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The Latest News, Articles, and Events in Signal Processing

Tufts University

Tufts University has an opening for a post-doctoral researcher to engage in a cross-cutting project focusing on the development of and use of Natural Language Processing (NLP) for social sciences applications. Recent advances, starting with the now classical word2vec approach to models built using attention and transformer networks such as BERT and GTP3 have shown tremendous potential for natural language modeling and automated interpretation.

Date: September 28, 2022
Chapter: Canadian Atlantic Chapter
Chapter Chair: Christopher J. Whitt
Title: What i wish i knew when i was an entry level engineer

It is my pleasure to announce that the IEEE Signal Processing Society (SPS) annual election will commence on 15 August, and your vote is more important than ever! This year, all eligible SPS Members will vote for the Regional Directors-at-Large for Regions 1-6 and 8 (term 1 January 2023 through 31 December 2024), and Members-at-Large (term 1 January 2023 through 31 December 2025) of the IEEE Signal Processing Society Board of Governors (BoG).

As the most widely-used spatial filtering approach for multi-channel signal separation, beamforming extracts the target signal arriving from a specific direction. We present an emerging approach based on multi-channel complex spectral mapping, which trains a deep neural network (DNN) to directly estimate the real and imaginary spectrograms of the target signal from those of the multi-channel noisy mixture. 

Date: October 10, 2022
Time: 9:00 AM ET (New York Time)
Title: Media Forensics and DeepFakes: An Overview
Registration | Full webinar details

With the rapid progress of recent years, techniques that generate and manipulate multimedia content can now provide a very advanced level of realism. The boundary between real and synthetic media has become very thin.

IEEE Signal Processing Magazine

This past May marked the beginning of our return to face-to-face events after almost three years of pandemic-forced virtual-only interactions. The first attempt was the 2022 ICASSP! Planning for large international events in the era of postpandemic uncertainty is not an easy undertaking. Of course, signal processing is all about dealing with uncertainty—and who would be better at planning than IEEE Signal Processing Society (SPS) people?

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.

IEEE Signal Processing Magazine

Designing a perfect filter (i.e., flat passband, sharp transition band, and highly suppressed stopband) is always the goal of digital signal processing practitioners. This goal is reachable if we make no consideration of implementation complexity. In other words, the challenge of designing a high-performance filter is to leverage the distortion tradeoff in the passband, transition band, and stopband. 

IEEE Signal Processing Magazine

Fourier theory is the backbone of signal processing (SP) and communication engineering. It has been widely used in almost all branches of science and engineering in numerous applications since its inception. However, Fourier representations such as Fourier series (FS) and Fourier transform (FT) may not exist for some signals that fail to fulfill a predefined set of Dirichlet conditions (DCs). 

IEEE Signal Processing Magazine

In separate projects, research teams based in Spain and Germany are using signal processing to help develop new ways of creating distortion-free brain imaging and detecting deceptively fake photographic images.

IEEE Signal Processing Magazine

This article discusses the contradiction between the exploding energy demand of artificial intelligence (AI) and the information and communication (ICT) industry as a whole and the parallel strong request for energy sobriety imposed by the need to mitigate the impact of climate change and the anticipated collapse of civilization as we know it.

IEEE Signal Processing Magazine

As humans, we cannot be indifferent to the increasing number of dramatic events taking place in the world: fires, tornadoes, floods, and - recently - the collapse of a huge block of the Marmolada glacier in the Italian Alps. All are clear evidence to the global warming of the Earth.

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.

Date: September 6, 2022
Time: 10:00 AM ET (New York Time)
Presenter: Dr. Nguyen Truong
Title: Decentralized Personal Data Management: A Blockchain-Based Solution
Registration | Full webinar details

Intelligent reflecting surface (IRS) has recently emerged as a promising paradigm for future wireless communications. Owing to its remarkable capability in reshaping the propagation environment, IRS has a great potential to boost spectral efficiency, mitigate interference, and enhance physical security. 

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.

This webinar presents ‘Tapestry’, a single-round pooled testing method with application to COVID-19 testing using quantitative Reverse Transcription Polymerase Chain Reaction (RT-PCR) that can result in shorter testing time and conservation of reagents and testing kits, at clinically acceptable false positive or false negative rates.

With the blooming of AI and machine-learning-based data-hungry applications and services, managing personal data and ensuring data privacy and security have become critical challenges.

This SPS webinar will introduce a novel data-driven cooperative localization and location data processing framework, called FedLoc, in line with the emerging machine learning and optimization techniques.

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