Share Your Innovation. Inspire Your Peers. Shape the Future.

Submit your abstract to the AWS Machine Learning University (AWS-MLU) Fall Symposium

Submit a Faculty Abstract
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Submission Deadline:

August 15, 2026

Notification of Acceptance:

August 20, 2026

Symposium Date:

September 22, 2026

Location:

Amazon Web Services, WAS16, 1770 Crystal Drive, Arlington, VA 22202

Available Poster Slots:

50

Understand Deeply. Think Critically. Build Intelligently.

We look forward to celebrating the creativity, scholarship, and novelty of faculty who are reimagining education through artificial intelligence.

Only 50 faculty posters will be accepted. We encourage early submission.

The AWS Machine Learning University (AWS-MLU) Fall Symposium invites faculty from all academic disciplines to submit abstracts for our Faculty Poster Session.
This session will highlight innovative teaching, research, curriculum development, workforce initiatives, and interdisciplinary collaborations that demonstrate how artificial intelligence and emerging technologies are transforming higher education. Whether your work is in engineering, business, education, healthcare, agriculture, the humanities, social sciences, or the arts, we encourage you to showcase ideas that advance student learning and prepare the next generation of innovators.

Faculty presenters will have the opportunity to:

Showcase innovative scholarship and educational practices

Exchange ideas with colleagues from institutions across the country

Build new interdisciplinary collaborations

Contribute to a growing national community advancing AI education

Inspire the next generation of faculty innovators

Suggested Topics

Submissions may include, but are not limited to:

AI in Teaching, Learning & Workforce Development

Generative AI in teaching and learning; curriculum innovation and instructional design; student workforce preparation and career readiness; faculty professional development and institutional transformation

AI-Enabled Research & Applications

AI-enabled research across disciplines; data science and machine learning applications; cybersecurity and AI; healthcare, agriculture, sustainability, and smart technologies; interdisciplinary AI projects

Responsible AI & Strategic Partnerships

Responsible and ethical AI; industry-academic partnerships

Abstract Guidelines

Celebrating the next generation of innovators who are ready to understand deeply, think critically, and build intelligently.

Maximum 300 words. Include:

Title

Author(s) and institution

Background or purpose

Methods or approach

Results or anticipated outcomes

Significance to higher education

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This symposium celebrates the ongoing collaboration between Amazon's Machine Learning University and institutions of higher education, including HBCUs, community colleges, and universities nationwide, fostering innovation, research excellence, and creating pathways for the next generation of AI/ML professionals.