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!