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Session Description

This workshop will provide engineering educators with practical tools and teaching strategies for integrating Edge AI into undergraduate curricula. The session begins with a presentation by Prof. Vijay Janapa Reddi (Harvard University), who will highlight the importance of AI at the edge and the pedagogical opportunities it presents for engineering programs.

Marcelo Rovai (UNIFEI - Federal University of Itajuba, Brazil) will then lead a hands-on tutorial using Arm-based development platforms, including the Seeed Studio Grove Vision AI Module V2 equipped with the Himax WiseEye2 HX6538 processor. Participants will learn how to train and deploy AI models for real-time computer vision applications, using open-source tools and low-cost hardware suitable for classroom use.

Who Should Attend:
Engineering faculty and instructors in electrical, computer, and software engineering programs; STEM educators seeking to introduce AI concepts through hands-on learning.

Special Equipment:
All necessary hardware will be provided for the hands-on session, including Arm-based vision modules and embedded development kits. Participants are encouraged to bring a laptop with USB-C support if they wish to replicate the exercises. At the end of the session, we'll give away 20 dev kits to participants thanks to the sponsorship from Himax and Seeed Studio..

About Prof. Vijay Janapa Reddi: Vijay Janapa Reddi is an Associate Professor at Harvard University in the School of Engineering and Applied Sciences. His research interests span the intersection of computer architecture and machine learning, with a focus on AI at the edge. He is a leading contributor to the MLCommons and MLPerf benchmarking initiatives and has worked closely with academia and industry to promote scalable, accessible AI education. Prof. Reddi previously held roles at AMD and Texas Instruments and received his Ph.D. from Harvard University.

About Prof. Marcelo Rovai: Marcelo José Rovai is a professor at the Federal University of Itajuba (UNIFEI), in Brazil, and a recognized leader in the education of practical embedded systems and IoT. He has authored numerous educational resources focused on AI at the edge and publishes on several popular technical sites dedicated to applied engineering tutorials. With a background in electrical engineering and data science, and over 40 years of experience in the technology sector, Prof. Rovai specializes in delivering hands-on, real-world engineering instruction in both academic and professional settings.

About Arm Education: The mission of the Education team at Arm is to help close education and skills gaps in Computer Engineering and STEM for the benefit of society. By drawing on Arm’s technological expertise, innovation and partner ecosystem, we provide content to help both teachers and learners achieve their objectives. In addition to the teaching and learning resources below, we enable access to IP, tools, and other support to universities for research enablement and work closely with academic and industry partners on research collaborations.