Research Projects
Compiler Optimization
Compiler optimization helps programmers obtain better performance out of target hardware platforms. But besides performance optimization, compilers may have different objectives in compiling and optimizing a program. Some project topics:
Compiler optimization for real-time systems: Optimize programs in a way that programs become more time predictable
Compiler optimization for machine learning: Provide portable and efficient code generation for machine learning models
Real-Time System Software
Real-time embedded systems range from autonomous cars to autonomous robots. Providing real-time guarantees in time-critical systems is essential for safety and reliability. Some project topics:
Real-time dynamic neural networks: Dynamically change or update neural networks based on dynamic real-time requirements
Real-time energy harvesting systems: Reflect energy availability in task scheduling for energy harvesting systems, which gather energy from the environment
Tiny Machine Learning
Tiny machine learning is to enable machine learning applications on small embedded systems, which normally use low-power microcontrollers. Deploying machine learning models is challenging for small embedded systems because of limited resources. Some project topics:
Tiny machine learning framework: Design a tiny machine learning framework for better resource management
Model compression: Design model compression and partitioning techniques for small embedded systems