Regular biography
Seulki Lee is a faculty member in the School of Electrical Engineering at KAIST. Their research focuses on embedded AI systems, particularly on resource-constrained real-time and embedded sensing systems capable of learning, adapting, and evolving. Lee leads the Embedded AI Lab, which is part of the School of Electrical Engineering and the Department of AI Systems at KAIST. The lab's work aims to enable Embedded Artificial Intelligence (Embedded AI or On-Device AI).
Scholar-generated biography
Seulki Lee is an Associate Professor at KAIST, specializing in Embedded Artificial Intelligence, Machine Learning, Mobile Computing, and Cyber-Physical Systems. Her research focuses on developing efficient and scalable AI solutions for resource-constrained environments, particularly in embedded and mobile systems. She explores techniques for on-device learning, energy-efficient neural network accelerators, and memory optimization for deep learning. Her work addresses challenges in real-time inference, training-free AI, and multitask learning for intelligent sensing systems. Lee's research also includes methods for improving the interpretability and adaptability of AI models in dynamic and battery-constrained settings.