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Syllabus / Agenda

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!¬†
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