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Towards Automatic Analysis of Sleep to Improve Health,” Jacky Mallett, Reykjavik University

Abstract: Applying artificial intelligence. and machine learning to multi-sensor inputs, offers the possibility of significantly improving detection and analysis of increasingly common conditions like sleep apnea that can cause major health issues over time if left untreated. One of the most important indicators of potential sleep apnea is pathological snoring, and in this talk we will review some of the challenges of working in this area, and the progress we have made with audio analysis of snoring and other signals as a basis for detecting apneic events.

Overview of HPC and AI Computing for COVID-19 in the United States,” RIck Stevens, Argonne National Laboratory

Abstract: In this talk, I’ll describe some of the ongoing work in the United States applying high-performance computing (HPC) and and artificial intelligence to COVID-19 related research. I will discuss the COVID-19 HPC consortium that joins U.S. supercomputing centers, computing and technology vendors and federal agencies to provide HPC cycles to the SARS-CoV-2/COVID-19 research community and to streamline access to resources via a single proposal mechanism. I’ll also discuss the collaboration among US DOE laboratory formed to apply advanced computing to the problem of developing molecular therapeutics for COVID-19.

This event is part of the Masterworks Webinar Series.

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