Join fellow Ohio State University researchers for a one-day, in-person event (agenda below) to discover how Amazon Web Service (AWS) cloud-powered AI and data platforms can accelerate your research. Learn to analyze research data through natural language queries, automate repetitive workflows, and conduct comprehensive research analysis—all while collaborating seamlessly with your team in secure, shared workspaces.
The training will feature use cases, demos, and hands-on workshops led by cloud experts and experienced researchers. This event introduces essential AWS services and AI-powered research tools through interactive sessions and demonstrations.Â
Whether you're new to the cloud or looking to optimize your existing cloud-based work, this event will provide the knowledge and skills to take full advantage of cloud computing for your research.
Who should attend
Researchers, faculty, scientists, and IT professionals. No experience with AWS is required.
Learn how OSU researchers are using AWS cloud to scale compute, reduce time-to-discovery, and tackle complex research challenges. This session showcases real examples of how cloud infrastructure helps OSU labs move faster from hypothesis to breakthrough.
Speakers:
   - Scott Friedman, Ph.D., leader for research computing solutions, AWSÂ
   - Huan Sun, Ph.D., Associate Professor, College of Engineering Innovation Scholar,      Computer Science and Engineering, OSUÂ
   - William S. Marras, Ph.D., Distinguished University Professor, Executive Director for     the Spine Research Institute, OSUÂ
   - Jonathan Dufour, Associate Applications Director, Spine Research Institute, OSUÂ
Discover how AI-powered chat agents and automated research capabilities can help you explore data, generate insights, and accelerate your research workflows—all through natural language conversations. Experience demos showing how Amazon Quick transforms complex data analysis into simple questions and answers, enabling researchers to focus on discovery rather than technical implementation.
Speaker: Jianjun Xu, Ph.D., principal solutions architect, AWSÂ
This session explores how cloud-based AI and ML services can accelerate research workflows, from foundation models and generative AI to purpose-built tools for data analysis, model training, and intelligent automation. We'll walk through real capabilities researchers can use today to streamline literature review, run large-scale experiments, and collaborate more effectively. Whether you're new to AI or already experimenting, you'll leave with a clear picture of what's possible.Â
Speaker: Scott Friedman, Ph.D., leader for research computing solutions, AWSÂ
Turn research complexity into repeatable, scalable workflows. In this session, you'll use Amazon Quick to build intelligent agents that surface answers from your own documents, automate multi-step processes so your team spends less time on manual tasks, and visualize key metrics in interactive dashboards — all configured to fit how your research actually runs.Â
Speaker: Jianjun Xu, Ph.D., principal solutions architect, AWSÂ
1/Workshop: Building Custom ML Models for Research
Learn how to train, fine-tune, and deploy machine learning models tailored to your research needs using Amazon SageMaker AI's integrated development environment. This hands-on workshop guides you through the complete ML lifecycle—from data preparation and model experimentation to production deployment—enabling you to build custom AI solutions that address your specific research challenges.Â
Speaker: Jianjun Xu, Ph.D., principal solutions architect, AWSÂ
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2/Workshop: Build your own Research Applications quickly using Kiro
In this hands-on workshop, you'll use Kiro to turn plain-English descriptions of your research needs into working applications—no programming experience required. Simply write what you want your tool to do, and Kiro's spec-driven approach handles the rest. You'll leave with a functional prototype and the confidence to build more on your own.
Speaker:Â Abhilash Thallapally, solutions architect, AWSÂ
