COVID-19

Ultraviolet semiconductor technologies for COVID-19 and beyond

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KAUST

COVID-19 is a wake-up call for public health and safety. Since the pandemic began, the ultraviolet (UV) technologies have been widely employed in numerous places to contain and eliminate the viruses. Although UV light is nonchemical and does not contaminate the environment, however, most of the UV light today comes from the toxic mercury lamps. In our lab and many institutions in the world, researchers are developing semiconductor-based UV technologies that are compact, reliable, and nontoxic. This seminar shows the research background and briefly discusses the research progress made by our team in a few key areas including material growth, physics, and device fabrication for UV lasers, LEDs, and photodetectors.

SIAM CSE21 (VIRTUAL) - Minisymposium on HPC Response to the COVID19 Pandemic

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KAUST

Abstract This minisymposium brings together experts in numerical simulation that have developed HPC software tools toward a better understanding coronavirus and the global COVID19 pandemic. Their recent results highlight the importance of computational science as a guiding tool that helps in uncovering the structure and mechanics of the viral spread as well as drastically reduces the number of candidate treatments that need laborious laboratory testing. From transformative medical advances to drug discovery driven by massively parallel supercomputing, this minisymposium will span a range of

A Rapid, Accurate and Machine-agnostic Segmentation and Quantification Method for CT-based COVID-19 Diagnosis

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KAUST

COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in developing diagnosis. Despite the various, urgent advances in developing artificial intelligence (AI)-based computer-aided systems for CT-based COVID-19 diagnosis, most of the existing methods can only perform classification, whereas the state-of-the-art segmentation method requires a high level of human intervention. In this talk, I will introduce our recent work on a fully-automatic, rapid, accurate, and machine-agnostic method that can segment and quantify the infection regions on CT scans from different sources. Our method is founded upon three innovations: 1) an embedding method that projects any arbitrary CT scan to a same, standard space, so that the trained model becomes robust and generalizable; 2) the first CT scan simulator for COVID-19, by fitting the dynamic change of real patients’ data measured at different time points, which greatly alleviates the data scarcity issue; and 3) a novel deep learning algorithm to solve the large-scene-small-object problem, which decomposes the 3D segmentation problem into three 2D ones, and thus reduces the model complexity by an order of magnitude and, at the same time, significantly improves the segmentation accuracy. Comprehensive experimental results over multi-country, multi-hospital, and multi-machine datasets demonstrate the superior performance of our method over the existing ones and suggest its important application value in combating the disease.

CT-based COVID-19 Diagnosis and Prognosis through Novel AI Model Development

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B2 L5 R5220

During the recent pandemic, urgent advances have been made by the scientific community in developing artificial intelligence (AI)-based computer-aided systems for CT-based COVID-19 diagnosis. In this talk, I will introduce our work on a fully-automatic, rapid, accurate, and machine-agnostic method that can segment and quantify the infection regions on CT scans from different sources.

AI that's built to save lives

1 min read ·
Associate Professor Xin Gao and his group have developed an artificial-intelligence (AI) based solution to help increase COVID-19 testing accuracy. Identifying cases of early stage infection has been particularly challenging for frontline clinicians. Gao's AI-based model, which aims to increase accuracy, has been put to immediate use at King Faisal Specialist Hospital (KFSH) in Riyadh.

Membrane makeover makes face mask reusable

1 min read ·
A polyimide membrane with regularly sized and spaced pores turns the N95 respirator into a reusable mask for protection against COVID-19.

A shock to the system

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The global, multifarious challenge posed by the COVID-19 pandemic has scientists tapping their wide-ranging fields of expertise to attack the problem on many fronts. Answering the call from KAUST President Tony Chan, and coordinated by the University's leadership team, KAUST researchers making up the Rapid Research Response Team (R3T) are turning this crisis into an opportunity to innovate.

Making the invisible, visible

1 min read ·
As bioscience and medicine progress, we are now able to live with diseases, which were once a death sentence. And we are rapidly discovering new interactions at the microscopic level that give us insight into the engines of life. However, as research gets more complicated, the layperson gets left further and further behind. Even those who trust the work of scientists can feel overwhelmed when attempting to read the latest research.

Studying COVID-19’s envelope protein

1 min read ·
A likeness between genes of the SARS and COVID-19 viruses could inform research into potential treatments.

How AI helps improve COVID-19 testing

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Following a call by President Tony Chan for KAUST PIs to contribute through their research capabilities to alleviate the COVID-19 pandemic, efforts coordinated by Donal Bradley, KAUST vice president for research, and Pierre Magistretti, KAUST dean of the Biological and Environmental Science and Engineering division, mobilized a group of faculty to form the Rapid Research Response Team (R3T).

Professor Hussain’s adaptive tech for distance learning project receives $20,000 in prize funding

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Muhammad Hussain, KAUST professor of electrical engineering and PI of the MMH Labs, was recently chosen as one of six finalists in the KAUST Community COVID-19 Innovation Challenge. The event, organized by KAUST Innovation and Economic Development, sought to generate community-driven solutions to challenges faced during the ongoing COVID-19 pandemic.

Peering under the hood of SARS-CoV-Two

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Microscope and protein data are incorporated into an easy-to-use-and-update tool that can model an organism’s 3D appearance.

KAUST startup tackles COVID using AI and robotics

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The COVID-19 pandemic has activated vital innovation and R&D initiatives to tackle the crippling effects, health ramifications, and overall impact of the coronavirus on global societies and economies. In recent months, the King Abdulaziz City for Science and Technology (KACST), based in Riyadh, Saudi Arabia, launched a COVID-19-themed virtual accelerator aimed at supporting talented innovators, aspiring entrepreneurs, and innovative small companies dedicated to finding solutions to mitigate the spread of the virus through protection, prevention, tracking/detection, and treatment solutions.

KAUST scientists develop virus mutation tracker

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​KAUST scientists have developed a user-friendly COVID-19 mutation tracking system, useful for authorities and scientists to quickly detect variants in their region, allowing them to make speedy policy and public health decisions.

Coronavirus testing made quick and easy

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New diagnostic technique could help contain the spread of COVID-19 and other viral outbreaks.

New paper accepted in Biometrics

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New paper accepted: Zhang, Z., Arellano-Valle, R. B., Genton, M. G., and Huser, R. (2022+), Tractable Bayes of skew-elliptical link models for correlated binary data, Biometrics, to appear [ PDF preprint].