Empowering a Million Minds on the Edge of AI

The EDGE AI FOUNDATION is launching a global certification and badge system designed to recognize real-world impact—on the job, in the lab, and across our community. Whether you’re completing foundational training, entering challenges, speaking at events, or collaborating in working groups, your contributions should be visible, verifiable, and valued.

Badges and certifications are more than digital stickers—they’re proof that you’re building what’s next at the edge.

Be one of the first to explore our certification path and earn your first badge.

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:

Brian Plancher (Chair) is an Assistant Professor of Computer Science at Dartmouth College. He was previously an Assistant Professor of Computer Science at Barnard College where he also held affiliate positions in the Department of Computer Science and Electrical Engineering at Columbia University.

Charlotte Frenkel, Assistant Professor, TU Delft. Charlotte Frenkel leads research at TU Delft on neuromorphic intelligence and hardware-algorithm co-design. Her work focuses on bridging bio-inspired approaches with engineering to develop ultra-low-power accelerators and on-device learning. She is a co-lead of the NeuroBench initiative and serves as a program co-chair for the tinyML Research Symposium.

Dhireesha Kudithipudi, Professor & Director of MATRIX AI Consortium, UT San Antonio. Dhireesha Kudithipudi is the Robert F. McDermott Endowed Chair at UTSA and the founding Director of the MATRIX AI Consortium. Her research focuses on neuromorphic computing, lifelong learning, and the development of energy-efficient AI architectures. She also leads the THOR project, the first open-access neuromorphic computing hub in the U.S.

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.

Francesco Conti, Associate Professor, University of Bologna. Francesco Conti is an Associate Professor at the University of Bologna and a core developer of the open-source PULP (Parallel Ultra-Low-Power) Platform. His research centers on novel hardware architectures and tools that enable deep learning on ultra-low-power systems-on-chip. He has spearheaded the development of over 15 SoC prototypes designed for energy-efficient perceptive intelligence.

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 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.

Marco Zennaro 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.

Morten Opprud Jakobsen, Researcher & Engineer, Aarhus University. Morten Opprud Jakobsen specializes in the practical implementation of Edge AI and energy-efficient embedded systems at Aarhus University. His research focuses on low-power communication and predictive maintenance through MEMS technology. He is dedicated to bridging the gap between theoretical machine learning and robust, field-deployable hardware.

Tinoosh Mohsenin is an Associate Professor in Electrical and Computer Engineering at Johns Hopkins University and Director of the Energy Efficient High Performance Computing Lab. Her research focus is on energy-efficient computing for signal processing and machine learning used in autonomous systems and smart health monitoring.

Winston Hsu, Professor, National Taiwan University. Winston Hsu is a Professor at National Taiwan University and a veteran AI technologist with experience leading industrial ventures like MobileDrive. His expertise spans computer vision, embodied AI, and the integration of perception and reasoning for automotive systems. He was the founding Director of the NVIDIA AI Lab at NTU and remains a leader in industrial AI collaboration.

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

• MLSYSBOOK.AI is an open source curriculum for edge AI
• Edge AI Engineering is an open source textbook
• Tech Diplomacy Academy by the Krach Institute
• Fundamentals of tinyML is a course on HarvardX
• Introduction to Embedded Machine Learning on Coursera
• Edge AI Fundamentals from Edge Impulse
• NVIDIA Graduate Fellowships
• Applied AI and Data Science Program at M.I.T.
• Professional Certificate in Machine Learning and Artificial Intelligence at UC Berkeley
• Machine Learning Crash Course from Google
• Introduction to machine learning from Microsoft
• Post Graduate Program in AI & Machine Learning: Business Applications from UT Austin