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Lee, Seulki

Lee, Seulki

Research Areas

AI & Machine Learning, Multimedia Signal Processing, Robotics & Control, Computer Architecture, Software Systems & Networking

Research

Embedded Systems, On-device AI, Machine Learning, Mobile and Sensing Systems, Real-time Computing

Laboratory

Embedded AI Lab

Building

Kim Beang-Ho KIM Sam-Youl ITC B/D (N1)

910

Extension

#7484

Email

seulki.lee@kaist.ac.kr

Website

https://sites.google.com/view/embeddedai

Research Group

Computer

division

Degree

Ph.D.(2021) University of North Carolina at Chapel Hill

Achievements

“Bayesian Code Diffusion for Efficient Automatic Deep Learning Program Optimization”, OSDI 2025
“CAFO: Feature-Centric Explanation on Time Series Classification”, KDD 2024
“Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks”, NeurIPS 2023
“On-NAS: On-Device Neural Architecture Search on Memory-Constrained Intelligent Embedded Systems”, SenSys 2023
“Fast and Scalable In-memory Deep Multitask Learning via Neural Weight Virtualization”, MobiSys 2020