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Credit: iStockphoto
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April 17, 2023Awardees, who represent 54 universities in 14 countries, have access to Amazon public datasets, along with AWS AI/ML services and tools.
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March 15, 2023The submission period opens March 15 and closes on April 26.
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January 30, 2023Awardees, who represent 25 universities in seven countries, have access to Amazon public datasets, along with AWS AI/ML services and tools.
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October 10, 2022Awardees represent more than 30 universities in eight countries. Recipients have access to Amazon public datasets, along with AWS AI/ML services and tools.
Research stories
View allAmazon has funded more than 400 projects—read about some of those here.
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May 24, 2023How ARA recipient Supreeth Shashikumar is using machine learning to help hospitals detect sepsis — before it’s too late.
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May 15, 2023ARA recipient Marinka Zitnik is focused on how machine learning can enable accurate diagnoses and the development of new treatments and therapies.
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November 28, 2022The professor of collective intelligence and robotics at the University of Cambridge earned a 2019 Amazon Research Award for “Learning Explicit Communication for Multi-Robot Path Planning”.
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BillionPhotos.com — stock.adobe.comAugust 16, 2022ARA recipient is using artificial intelligence to help doctors make decisions based on radiological data.
The ARA support has substantially helped crystallize our group's formulations and algorithms for fairness in cloud services, efficiency in online advertising, and the tradeoffs between efficiency and fairness in online services.
Aravind Srinivasan, University of Maryland, College Park
This project has a huge impact on the society and healthcare because it allows to provide timely and accurate diagnosis of neurological speech disorders (e.g., dystonia). The MLRA enabled us to use cutting-edge GPU capabilities to develop, train and validate our deep learning models for diagnosis of neurological speech disorders.
Kristina Simonyan, Harvard Medical School
The generous award provide by AWS has helped us to pump-prime novel research on the interface of climate science and machine learning. It also allowed us to make significant progress in understanding the benefits of using the cloud for ML focused climate research (on clouds).
Philip Stier, University of Oxford
The award allowed us to scale up our experiments to learn traffic smoothing algorithms in high fidelity simulations. The RL policies learned from the work are now in the process of being transferred to actual vehicles for field operational testing on California freeways.
Alexandre Bayen, University of California, Berkeley
