Accurate and rich representation of roads in a map is critical for safe and efficient navigation experience. Often, open source road data is incomplete and manually adding roads is labor intensive and consequently expensive. In this paper, we propose RING-Net, an approach for Road INference from…
Classifying trip modalities, i.e. driving, walking, etc., from GPS trajectories is one of the fundamental tasks for urban mobility analytics. It can be used for efficient route planning, human activity recognition, and public transportation design where understanding the time and location of…
We study semi-supervised learning (SSL) for vision transformers (ViT), an underexplored topic despite the wide adoption of the ViT architectures to different tasks. To tackle this problem, we use a SSL pipeline, consisting of first un/self-supervised pre-training, followed by supervised…
In learning-to-rank problems, a privileged feature is one that is available during model training, but not available at test time. Such features naturally arise in merchandised recommendation systems; for instance, “user clicked this item” as a feature is predictive of “user purchased this item” in…
The Neural Information Processing Systems (NeurIPS) annual meeting fosters the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. The core focus is peer-reviewed novel research which is presented and discussed in the general session, along with invited talks by leaders in their fields.
Built-in radar technology, deep domain adaptation for sleep stage classification, and low-latency incremental sleep tracking enable Halo Rise to deliver a seamless, no-contact way to help customers improve sleep.
Discover the latest news about scientific innovation at Amazon. Find articles from scientists and researchers about artificial intelligence, machine learning, and more.
Developing advanced techniques to analyze behavioral patterns, lexical matches, and semantic matches to surface the most relevant recommendations in response to your queries.
The Alexa Prize is a series of competitions for university students dedicated to accelerating the field of artificial intelligence. Participating teams will advance several areas of AI through generalizable methodologies such as continuous learning, teachable AI, multimodal understanding, and reasoning.Through the innovative work of students, Amazon Alexa customers will have novel, engaging interactions. And, the immediate feedback from these customers will help students improve their algorithms much faste
The Amazon Summer Undergraduate Research Experience (SURE) aims to increase diversity in science and engineering fields by providing students from historically underrepresented communities with a unique summer research experience at a top-tier university. For more information, please visit our frequently asked questions section.
Amazon Research Awards was founded in 2015 and merged with AWS Machine Learning Research Awards (MLRA) in 2020. The ARA program offers unrestricted cash awards and AWS Promotional Credits to fund research at academic institutions and non-profit organizations in areas that align with our mission to advance customer-obsessed science.
We hire world-class academics as Amazon Scholars and Amazon Visiting Academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities. Learn more about our programs, and how to apply.
Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds in artificial intelligence and related fields.
Amazon offers internships year round, and projects will depend on a student’s area of research and interest, as well as the team they're placed. View our available internships.
Focusing on the automation of formal logical reasoning to raise the bar on the security, durability, availability, and quality of Amazon’s products and services.
Science at Amazon enables new customer experiences and addresses existing customer challenges whenever there is limited or no existing prior art. It complements the company’s engineering and product disciplines, and is critical to all Amazon businesses focused on delivering increased customer value.