Empowering a Million Minds on the Edge of AI

Empowering a Million Minds on the Edge of AI

Join the movement to make edge AI knowledge accessible to all—through live workshops, real-world challenges, and learning experiences designed for the future.

The EDGE AI FOUNDATION is a vibrant, global community. Discover the best way for you to connect and contribute.

EDGE AI FOUNDATION is Creating the Movement

The EDGE AI FOUNDATION is not just launching a program—it’s building a movement to reshape how edge AI is taught, understood, and applied. We're making leading-edge knowledge accessible to students, professionals, and developers around the world. Backed by a global network of over 100 Fortune 500 technology partners—and with more than 600,000 people already reached—we’re building a hands-on learning ecosystem designed to meet the urgency and opportunity of this era. Our vision reshapes edge AI education with an engaging, hands-on approach that includes:
teaching

EDGE AI Scholarship Program

The EDGE AI SCHOLARSHIP program underwrites programs to accelerate learning and literacy around the world, including fellowships, travel grants and education programs like the one we recently supported in Malawi:

 

 

The EDGE AI Scholarship Program is supported by our Strategic Partners as well as our Scholarship Partners who provide value-added services to our community while contributing to the growth of the fund.

 

EDGE AI Labs

EDGE AI Labs

EDGE AI Labs provides a resource to leverage community code for datasets, models and blueprints for solutions. Hosted by embedUR’s ModelNiova platform, it’s a great place to start for professional and academic developers

  • Provide a level-playing field for academia/Industry researchers to be able to evaluate the quality/perf of their proposed algorithms/NNs
  • Focus on a high-quality community-curated open-source datasets for training of small NNs with dedicated tasks
  • Provide a platform to share algorithms/NNs/Papers using these datasets and build on each other’s work
EDGE AI Labs
EDGE AI Challenges

EDGE AI Challenges

A worldwide challenge series that takes a flexible, solutions-centric approach to edge AI. This program pushes the boundaries of innovation, encouraging participants from around the world.

 

We are partnering with Hackster and embedUR to bring these challenges to a worldwide ecosystem of developers in industry and academia.

 

Check out out latest EDGE AI Challenge -> Wake Vision 2!

EDGE AIP - Academia and Industry Partnership

The EDGE Academia-Industry Partnership (EDGE AIP) now bridges the academic world and edge AI industry by empowering everyone with knowledge and opportunities from tinyML to the edge of AI.

EDGE Academia-Industry Leadership team navigates the educational opportunities for our community worldwide:

 

Vijay Janapa Reddi (co-chair) is an Associate Professor in John A. Paulson School of Engineering and Applied Sciences at Harvard University. Prior to joining Harvard, he was an Associate Professor at The University of Texas at Austin in the Department of Electrical and Computer Engineering.

Hajar Mousannif is an associate professor and coordinator of the Master program in Data Science within the department of computer science at the Faculty of Sciences Semlalia (Cadi Ayyad University, Morocco). She holds a PhD degree in computer Sciences on her work on Wireless Sensor Networks and Vehicular Networks.

Marcelo Rovai (co-chair of tinyML4D) was born in São Paulo and holds a Master’s degree in Data Science by the UDD in Chile, as well as an MBA by IBMEC (INSPER) in Brazil. He graduated in 1982 as an Engineer from UNIFEI with a specialization from Poli/USP, both institutions are located in Brazil.

Marian Verhelst is a professor at the Electrical Engineering department of KU Leuven. Previously, from 2008 till 2011, she worked as a research scientist in the Radio Integration Research Lab of Intel Labs, Hillsboro OR, and in 2005 she was a visiting scholar at the Berkeley Wireless Research Center(BWRC) of UC Berkeley.

Brian Plancher (co-chair) (chair of tinyML EDU) is an Assistant Professor of Computer Science at Barnard College, Columbia University, where he leads the Accessible and Accelerated Robotics Lab (A²R Lab). He holds affiliate positions in the Department of Computer Science and Electrical Engineering at the Fu Foundation School of Engineering and Applied Science, Columbia University.

Eiman Kanjo Prof. Eiman Kanjo is a Professor of Pervasive Sensing and the head of the Smart Sensing Lab. Eiman has been appointed as the Provost’s Visiting Professor in tinyML at Imperial College London starting- October 2023. She has recently been honored as one of the Top 50 Women in Engineering by the Women in Engineering Society.

Marco Zennaro (co-chair of tinyML4D) is a research scientist at the Abdus Salam International Centre for Theoretical Physics in Trieste, Italy, where he coordinates the Science, Technology and Innovation Unit. He received his PhD from the KTH-Royal Institute of Technology, Stockholm, and his MSc degree in Electronic Engineering from the University of Trieste.

Tinoosh Mohsenin is an Associate Professor in Electrical and Computer Engineering in Whiting School of Engineering and Affiliate faculty at the Johns Hopkins . She is also the Director of the Energy Efficient High Performance Computing Lab. Before joining Johns Hopkins, she spent 11 years at the University of Maryland Baltimore County in the Department of Computer Science and Electrical Engineering. Prof. Mohsenin’s research focus is on energy efficient computing for signal processing and machine learning used in, multi-agent aerial and gourd autonomous systems, human and machine teaming, wearable smart health monitoring. She received her PhD from University of California, Davis in 2010 and MSc degree from Rice University in 2004, both in Electrical and Computer Engineering.

EDGE AI Career

In cooperation with our Scholarship Partner 5V Tech, EDGE AI Career is a new livestream series dedicated to exploring and illuminating career paths in the edge AI industry. We’ll bring insights from industry leaders, share success stories, and provide guidance on how to thrive in this rapidly evolving field.

 

 

As part of our commitment to building a strong talent pipeline, we’ll also connect learners with career opportunities, industry mentors, and hiring partners looking for the next wave of edge AI innovators.

EDGE AI Career Playlist

EDGE AI Learning Resources

Here are more resources to help you get started on your learning journey with edge AI:

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