NOTE: agenda is tentative and subject to change
- Introduction
- Embedded AI Definition, Advantages, Challenges, and Applications
- Core Concepts / Programming Frameworks / Platforms / Tools
- Fundamentals of Embedded Systems and AI/ML
- TinyML (Vijay Janapa Reddi, Harvard)
- Hardware AI/ML Accelerators (Zhangxi Tan, RIOS Lab)
- Embedded Data (Jorge Ortiz, Rutgers)
- Federated Learning and Mobile AI (Nic Lane, Cambridge)
- Scalable AI (Matt Welsh, OctoML)
- Applications in Embedded AI
- Acoustic AI (Stephen Xia)
- Embedded AI in Structures (Shijia Pan, UC Merced)
- Federated Learning in Health AI (Robert Dickerson, Babylon Health)
- Entrepreneurship (Thomas Cheng, Brava)
- Hands-on Tutorials
- TensorFlow Lite Micro (Yanchen Liu)
- TVM/uTVM (Gavin Uberti, OctoML)
- Project
- Your turn!