Tag: AWS Cloud Credit for Research

About 4.5 million electroencephalogram (EEG) tests are performed in the US each year. That’s more than if every person in Oregon, Connecticut, or Iowa got an EEG. Because they provide insights into brain activity and not just structure, EEGs are one of the most common tests ordered by doctors to help make a diagnosis for people with brain problems. The Brain Data Science Platform (BDSP), hosted on Amazon Web Services (AWS), is increasing EEG accessibility through cooperative data sharing and research enabled by the cloud. Read this post to learn more.

The cloud is changing the way we do research—accelerating the pace of innovation, democratizing access to data, and allowing researchers and scientists to scale, work collaboratively, and make new discoveries from which we may all benefit. Researchers from around the world look to the AWS Cloud for customer-focused, pioneering, and secure solutions for their toughest challenges. Discover how customers in Latin America and Canada use AWS for research.

At AWS, we know these are challenging times and we remain committed to supporting nonprofits. This blog post outlines a sampling of programs and resources for nonprofits, including grants and credits, open data access, cloud training, educational events, and more, designed to enable organizations of all sizes to overcome barriers to technology adoption, while enhancing the scale, performance, and capabilities of mission operations.

The AWS Cloud Credit for Research Program launched a new opportunity for Amazon Scholars and Amazon Visiting Academics to apply for AWS Promotional Credit to accelerate innovation through cloud technology. Amazon Scholars are world-class academics and Amazon Visiting Academics are pre- to newly-tenured academics, selected to tackle real-world technical challenges as they continue to teach and conduct research at their universities. AWS Promotional Credit is offered through this initiative is to support the awardees’ impactful university research that’s distinct from their work at Amazon.

About 40 million MRI scans are performed in the United States every year. MRIs are a valuable part of diagnostic plans, but as they exist today, they may not always be a part of a patient’s care plan. A research team at the New York University (NYU) Langone Center set out to make MRIs more accessible for more patients by using artificial intelligence (AI), machine learning (ML), and the power of cooperative open data sharing.

Before the Event Horizon Telescope project released the first-ever picture of a black hole in 2019, nobody had ever seen one. Black holes are a region of space with a gravitational pull so strong that nothing—not even light—can escape them. The cloud is helping accelerate research into black holes.

Be it aspirin for headache, or statin for cholesterol, or amoxicillin as an antibiotic, there are small molecules that we refer to as drugs that can offer therapeutic remedy. Given the range of possible molecule to protein combinations, finding the right small molecule that is able to bind strongly to a certain target site and inhibit its function is a time-intensive and challenging feat. Enter VirtualFlow, a new open-source software that performs screens, essentially matchmaking between molecules and proteins. Harvard Medical School researchers developed the VirtualFlow platform that tests compounds through computer simulations. Using AWS and an AWS Cloud Credit for Research grant, the researchers demonstrated that VirtualFlow is able to run on the cloud.

In 2014, the Wall Lab at Stanford University sought to answer one of the most pressing questions in neuroscience: What genes influence autism spectrum disorder (ASD)? According to the Centers for Disease Control (CDC), this neurodevelopmental disorder affects roughly one in 54 children in America and is on the rise—nearly tripling since 1992. In the lab’s study of ASD genetics, they chose the cloud—and a unique experimental approach—to speed the time to science.

Forest wildfire risk is increasing in the western United States. In the past five decades, large wildfire frequency and the area destroyed have risen by more than four and six times, respectively. The increased risk posed by wildfires has prompted scientists to try to assess wildfire risk to help inform whether to move people to safety before disastrous wildfires occur.