34 Amazon Research Awards Build on Trainium recipients announced
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Researchers from 30 universities received Build on Trainium awards to advance Responsible AI on AWS Trainium infrastructure.
34 Amazon Research Awards Build on Trainium recipients announced
Amazon announces recipients of the Build on Trainium program, a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
By Amazon Research Awards team
August 5, 2026
5 min read
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Build on Trainium is a $110 million credit program focused on AI research and university education aimed to support the next generation of innovation and development on AWS Trainium . The program provides compute credits to novel AI research on Trainium, investing in leading academic teams to build innovations in critical areas including new model architectures, ML libraries, optimizations, large-scale distributed systems, and more.
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This announcement includes awards funded under the Fall 2025 Build on Trainium: Responsible AI call for proposals. Proposals were reviewed for the quality of their scientific content and their potential to impact both the research community and society. This cycle’s focus on Responsible AI invited proposals addressing five priority topics: AI safety and alignment, multi-lingual language models, representation engineering, sustainability and small language models, and deep learning models for synthetic data generation—all leveraging AWS Trainium infrastructure. The recipients have access to more than 700 Amazon public datasets and can utilize AWS AI/ML services and tools through their AWS Promotional Credits, are assigned an Amazon research contact who offers consultation and advice, and benefit from AWS Trainium resources, such as tutorials and hands-on sessions.
Build on Trainium represents AWS's commitment to democratizing AI research through collaborative partnership with academia.
Yida Wang, principal applied scientist
"Build on Trainium gives the next wave of AI researchers powerful, scalable access to Amazon's purpose-built AI chips, so the only limit is their imagination, not their compute budget," said Yida Wang, AWS AI Principal Applied Scientist. "By leveraging the support from Build on Trainium, University of Illinois Urbana-Champaign researchers are studying topology-aware parallelization strategies for large-scale mixture-of-experts models with as many as one trillion parameters on up to 1,024 Trainium chips. At the University of Washington, researchers are developing an inference-optimization framework that raises token efficiency for everyone building on Trainium, with the goal to deliver portable, high-performance LLM inference on Trainium."
Recipient
University
Research title
Wei Bao
The University of Sydney
FACTOR: Federated Adversarial Co-Training with Textual Gradient for LLM Security and Robustness
Viveck Cadambe
Georgia Institute of Technology
Leveraging Public-Private Mixtures For...
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notability 3.0/10Routine award announcement, low traction.