KAIST EPIC Lab

Welcome to EPIC LAB at KAIST EE/AIS

Embedded Processor & Intelligent Computing (EPIC) Lab is a research group at the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, jointly affiliated with the School of Electrical Engineering and the Department of AI Systems. EPIC Lab develops efficient hardware-software building blocks for application-specific embedded processors, with a focus on intelligent computing across a broad range of emerging workloads.

Our research spans cross-disciplinary topics including algorithms, computer architectures, and system-on-chip (SoC) designs. We currently focus on energy-efficient processors for compressed machine learning models, high-performance baseband processors for next-generation communication systems, and emerging IoT platforms for human-centric applications.

Latest News

[2026/06] Our paper enetitled "Retention-resilient ECRAM-PIM training system with device-algorithm-controller co-design," has been accepted for publication in the IEEE Transactions on Circuits and Systems I: Regular Papers.

[2026/05] Our project on multi-core RISC-V architecture has received the Best Research Award from the Samsung Neural Processing Research Center (NPRC).

[2026/04] Our paper entitled "Machine learning assisted tilt/azimuth estimation for passive stylus pens using position-based model selection" has been accepted for publication in the IEEE Access.

[2026/04] Our paper entitled "StylusNet: ML-based coordinate extractor for EMR stylus touch devices" has been accepted for publication in the IEEE Sensors Journal.

[2026/03] Prof. Lee has received the Outstanding Lecture Award from KAIST EE.

[2026/03] Our paper entitled "CL-PLAC: A generalized design framework for nonlinear functions using comparator-less piecewise linear approximate computation" has been accepted for publication in the IEEE Transactions on Circuits and Systems for Artificial Intelligence.

[2026/02] Our paper entitled "Asymmetric KV cache compression using state-aware sparsity and quantization" has been accepted for publication in the IEEE Transactions on Circuits and Systems for Artificial Intelligence.