A 0.8V 82.9µW In-Ear BCI Controller System with 8.8 PEF EEG Instrumentational Amplifier and Wireless BAN Transceiver. - Jaehyuk Lee; Kyoung-Rog Lee; Unsoo Ha; Ji-Hoon Kim 004; Kwonjoon Lee; Hoi-Jun Yoo (VLSI Circuits, 2018)

An Ultra-Low-Power Analog-Digital Hybrid CNN Face Recognition Processor Integrated with a CIS for Always-on Mobile Devices. - Ji-Hoon Kim 004; Changhyeon Kim; Kwantae Kim; Hoi-Jun Yoo (ISCAS, 2019)

A 0.5V 9.26μW 15.28mΩ/√Hz Bio-Impedance Sensor IC With 0.55° Overall Phase Error. - Kwantae Kim; Ji-Hoon Kim 004; Surin Gweon; Jiwon Lee; Minseo Kim; Yongsu Lee; Soyeon Kim; Hoi-Jun Yoo (ISSCC, 2019)

A 0.8-V 82.9- $ mu$ W In-Ear BCI Controller IC With 8.8 PEF EEG Instrumentation Amplifier and Wireless BAN Transceiver. - Jaehyuk Lee; Kyoung-Rog Lee; Unsoo Ha; Ji-Hoon Kim 004; Kwonjoon Lee; Surin Gweon; Jaeeun Jang; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2019)

Z-PIM: An Energy-Efficient Sparsity Aware Processing-In-Memory Architecture with Fully-Variable Weight Precision. - Ji-Hoon Kim 004; Juhyoung Lee; Jinsu Lee; Hoi-Jun Yoo; Joo-Young Kim 001 (VLSI Circuits, 2020)

A 0.5-V Sub-10-μW 15.28-mΩ/√Hz Bio-Impedance Sensor IC With Sub-1° Phase Error. - Kwantae Kim; Ji-Hoon Kim 004; Surin Gweon; Minseo Kim; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2020)

Accelerating Large-Scale Nearest Neighbor Search with Computational Storage Device. - Ji-Hoon Kim 004; Yeo-Reum Park; Jaeyoung Do; Soo Young Ji; Joo-Young Kim 001 (FCCM, 2021)

An Energy-efficient Floating-Point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory. - Juhyoung Lee; Jihoon Kim 004; Wooyoung Jo; Sangyeob Kim; Sangjin Kim; Donghyeon Han; Jinsu Lee; Hoi-Jun Yoo (HCS, 2021)

OmniDRL: An Energy-Efficient Mobile Deep Reinforcement Learning Accelerators with Dual-mode Weight Compression and Direct Processing of Compressed Data. - Juhyoung Lee; Sangyeob Kim; Ji-Hoon Kim 004; Sangjin Kim; Wooyoung Jo; Donghyeon Han; Hoi-Jun Yoo (HCS, 2021)

A 13.7 TFLOPS/W Floating-point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory. - Juhyoung Lee; Jihoon Kim 004; Wooyoung Jo; Sangyeob Kim; Sangjin Kim; Jinsu Lee; Hoi-Jun Yoo (VLSI Circuits, 2021)

Z-PIM: A Sparsity-Aware Processing-in-Memory Architecture With Fully Variable Weight Bit-Precision for Energy-Efficient Deep Neural Networks. - Ji-Hoon Kim 004; Juhyoung Lee; Jinsu Lee; Jaehoon Heo; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2021)

A 0.82 μW CIS-Based Action Recognition SoC With Self-Adjustable Frame Resolution for Always-on IoT Devices. - Junha Ryu; Gwangtae Park; Dongseok Im; Ji-Hoon Kim 004; Hoi-Jun Yoo (IEEE Trans. Circuits Syst. II Express Briefs, 2021)

A Dual-Mode Similarity Search Accelerator based on Embedding Compression for Online Cross-Modal Image-Text Retrieval. - Yeo-Reum Park; Ji-Hoon Kim 004; Jaeyoung Do; Joo-Young Kim 001 (FCCM, 2022)

Trinity: End-to-End In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics. - Ji-Hoon Kim 004; Seunghee Han; Kwanghyun Park 001; Soo-Young Ji; Joo-Young Kim 001 (HCS, 2022)

Accelerating Large-Scale Graph-based Nearest Neighbor Search on a Computational Storage Platform. - Ji-Hoon Kim 004; Yeo-Reum Park; Jaeyoung Do; Soo Young Ji; Joo-Young Kim 001 (CoRR, 2022)

OmniDRL: An Energy-Efficient Deep Reinforcement Learning Processor With Dual-Mode Weight Compression and Sparse Weight Transposer. - Juhyoung Lee; Sangyeob Kim; Sangjin Kim; Wooyoung Jo; Ji-Hoon Kim 004; Donghyeon Han; Hoi-Jun Yoo (IEEE J. Solid State Circuits, 2022)

ECIM: Exponent Computing in Memory for an Energy-Efficient Heterogeneous Floating-Point DNN Training Processor. - Juhyoung Lee; Jihoon Kim 004; Wooyoung Jo; Sangyeob Kim; Sangjin Kim; Hoi-Jun Yoo (IEEE Micro, 2022)

A 26.55TOPS/W Explainable AI Processor with Dynamic Workload Allocation and Heat Map Compression/Pruning. - Junsoo Kim 002; Geonwoo Ko; Ji-Hoon Kim 004; Changha Lee; Taewoo Kim 003; Chan-Hyun Youn; Joo-Young Kim 001 (CICC, 2023)

Accelerating Large-Scale Graph-Based Nearest Neighbor Search on a Computational Storage Platform. - Ji-Hoon Kim 004; Yeo-Reum Park; Jaeyoung Do; Soo-Young Ji; Joo-Young Kim 001 (IEEE Trans. Computers, 2023)

South Korea's Nationwide Effort for AI Semiconductor Industry. - Ji-Hoon Kim 004; Sungyeob Yoo; Joo-Young Kim 001 (Commun. ACM, 2023)

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics. - Ji-Hoon Kim 004; Seunghee Han; Kwanghyun Park 001; Soo-Young Ji; Joo-Young Kim 001 (IEEE Access, 2024)

EPU: An Energy-Efficient Explainable AI Accelerator With Sparsity-Free Computation and Heat Map Compression/Pruning. - Junsoo Kim 002; Seunghee Han; Geonwoo Ko; Ji-Hoon Kim 004; Changha Lee; Taewoo Kim 003; Chan-Hyun Youn; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2024)

EXION: Exploiting Inter-and Intra-Iteration Output Sparsity for Diffusion Models. - Jaehoon Heo; Adiwena Putra; Jieon Yoon; Sungwoong Yune; Hangyeol Lee; Ji-Hoon Kim 004; Joo-Young Kim 001 (HPCA, 2025)

SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models. - Jinho Yang; Ji-Hoon Kim 004; Joo-Young Kim 001 (CoRR, 2025)