LightNorm: Area and Energy-Efficient Batch Normalization Hardware for On-Device DNN Training. - Seock-Hwan Noh; Junsang Park; Dahoon Park; Jahyun Koo 002; Jeik Choi; Jaeha Kung (ICCD, 2022)

DBPS: Dynamic Block Size and Precision Scaling for Efficient DNN Training Supported by RISC-V ISA Extensions. - Seunghyun Lee; Jeik Choi; Seock-Hwan Noh; Jahyun Koo 002; Jaeha Kung (DAC, 2023)

All-rounder: A flexible DNN accelerator with diverse data format support. - Seock-Hwan Noh; Seungpyo Lee; Banseok Shin; Sehun Park; Yongjoo Jang; Jaeha Kung (CoRR, 2023)

FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support. - Seock-Hwan Noh; Jahyun Koo 002; Seunghyun Lee; Jongse Park; Jaeha Kung (IEEE Trans. Computers, 2023)

FlexNeRFer: A Multi-Dataflow, Adaptive Sparsity-Aware Accelerator for On-Device NeRF Rendering. - Seock-Hwan Noh; Banseok Shin; Jeik Choi; Seungpyo Lee; Jaeha Kung; Yeseong Kim (ISCA, 2025)

All-Rounder: A Flexible AI Accelerator With Diverse Data Format Support and Morphable Structure for Multi-DNN Processing. - Seock-Hwan Noh; Seungpyo Lee; Banseok Shin; Sehun Park; Yongjoo Jang; Jaeha Kung (IEEE Trans. Very Large Scale Integr. Syst., 2025)

Jack Unit: An Area- and Energy-Efficient Multiply-Accumulate (MAC) Unit Supporting Diverse Data Formats. - Seock-Hwan Noh; Sungju Kim; Seohyun Kim; Daehoon Kim; Jaeha Kung; Yeseong Kim (CoRR, 2025)

FlashVault: Versatile In-NAND Self-Encryption with Zero Area Overhead. - Seock-Hwan Noh; Hoyeon Lee; Junkyum Kim; Junsu Im; Jay H. Park; Sungjin Lee 001; Sam H. Noh; Yeseong Kim; Jaeha Kung (CoRR, 2025)