NOTE: agenda is tentative and subject to change
- Introduction
- Embedded AI Definition, Advantages, Challenges, and Applications (Jiang)
- Core Concepts / Programming Frameworks / Platforms / Tools
- Fundamentals of Embedded Systems and AI/ML (Jiang)
- TinyML (Song Han, MIT)
- Machine Learning Sensors (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)
- Applications in Embedded AI
- Acoustic AI (Stephen Xia)
- Robotic AI (Boyuan Chen)
- Physical Knowledge-Informed AI (Shijia Pan, UC Merced)
- Hands-on Tutorials
- TensorFlow Lite Micro (Jingping Nie, Scott Zhao)
- Flower (Pedro Porto Buarque de Gusmão)
- TVM/uTVM (Gavin Uberti)
- Project
- Your turn!
Weekly Schedule
Date | Topic |
1/23 | Course introduction and logistics |
1/30 | Fundamentals of Embedded Systems and AI/ML |
2/6 | Tutorial: TensorFlow Lite Micro |
2/13 | Hardware AI/ML Accelerators (Zhangxi Tan, RIOS Lab) |
2/20 | ML Sensors (Vijay Janapa Reddi, Harvard) |
2/27 | Federated Learning and Mobile AI (Nic Lane, Cambridge) |
3/6 | FLOWER Tutorial |
3/13 | Spring Recess |
3/20 | Acoustic AI (Stephen Xia) |
3/27 | TinyML (Song Han, MIT) |
4/3 | Tutorial: TVM/uTVM |
4/10 | Robotic AI: From Narrow Robots to General Robots |
4/17 | Physical Knowledge-Informed Learning Adaptation for Embedded AI (Shijia Pan, UC Merced) |
4/24 | Embedded Data (Jorge Ortiz, Rutgers) |
5/1 | Project demonstrations |