Efficient Computing Lab.

Welcome to the Efficient Computing Lab. We focus on energy efficiency, system optimization, user experience, and sustainable tech solutions. Our research interests are the followings::

• Model Compression: We are dedicated to improving the performance of machine learning models, particularly through the use of model compression techniques. This involves reducing the complexity of existing models while maintaining their performance or even enhancing it. We are interested in exploring different methods of model compression, such as pruning, quantization, and knowledge distillation. By doing so, we aim to make these models more accessible and affordable to implement, even in resource-constrained environments.
• AI Compiler: Our interest also extends to the field of AI compilers, with a focus on optimizing and automating the process of translating high-level AI algorithms into efficient low-level machine codes. We believe that efficient AI compilers can significantly reduce the amount of computational power required, thus lowering energy consumption. Additionally, they can improve the speed of execution, thereby enhancing the overall user experience. Our aim is to investigate new compiler techniques, optimization methods, and tools that will make AI systems more efficient, sustainable, and widely applicable.

We are looking for highly motivated students. If you are interested, please send cv to leejaymin_at_etri_dot_re_dot_kr.