PowerField: a transient temperature-to-power technique based on Markov random field theory. - Seungwook Paek; Seok-Hwan Moon; Wongyu Shin; Jaehyeong Sim; Lee-Sup Kim (DAC, 2012)

PowerField: A Probabilistic Approach for Temperature-to-Power Conversion Based on Markov Random Field Theory. - Seungwook Paek; Wongyu Shin; Jaehyeong Sim; Lee-Sup Kim (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2013)

Timing error masking by exploiting operand value locality in SIMD architecture. - Jaehyeong Sim; Jun-Seok Park; Seungwook Paek; Lee-Sup Kim (ICCD, 2014)

14.6 A 1.42TOPS/W deep convolutional neural network recognition processor for intelligent IoE systems. - Jaehyeong Sim; Jun-Seok Park; Minhye Kim; Dongmyung Bae; Yeongjae Choi; Lee-Sup Kim (ISSCC, 2016)

A 5-Gb/s 2.67-mW/Gb/s Digital Clock and Data Recovery With Hybrid Dithering Using a Time-Dithered Delta-Sigma Modulator. - Taeho Lee 001; Yong-Hun Kim; Jaehyeong Sim; Jun-Seok Park; Lee-Sup Kim (IEEE Trans. Very Large Scale Integr. Syst., 2016)

A Kernel Decomposition Architecture for Binary-weight Convolutional Neural Networks. - Hyeonuk Kim; Jaehyeong Sim; Yeongjae Choi; Lee-Sup Kim (DAC, 2017)

SENIN: An energy-efficient sparse neuromorphic system with on-chip learning. - Myung-Hoon Choi; Seungkyu Choi; Jaehyeong Sim; Lee-Sup Kim (ISLPED, 2017)

Energy-Efficient Design of Processing Element for Convolutional Neural Network. - Yeongjae Choi; Dongmyung Bae; Jaehyeong Sim; Seungkyu Choi; Minhye Kim; Lee-Sup Kim (IEEE Trans. Circuits Syst. II Express Briefs, 2017)

NID: processing binary convolutional neural network in commodity DRAM. - Jaehyeong Sim; Hoseok Seol; Lee-Sup Kim (ICCAD, 2018)

TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training. - Seungkyu Choi; Jaehyeong Sim; Myeonggu Kang; Lee-Sup Kim (ISLPED, 2018)

A 47.4µJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices. - Seungkyu Choi; Jaehyeong Sim; Myeonggu Kang; Yeongjae Choi; Hyeonuk Kim; Lee-Sup Kim (A-SSCC, 2019)

NAND-Net: Minimizing Computational Complexity of In-Memory Processing for Binary Neural Networks. - Hyeonuk Kim; Jaehyeong Sim; Yeongjae Choi; Lee-Sup Kim (HPCA, 2019)

eSRCNN: A Framework for Optimizing Super-Resolution Tasks on Diverse Embedded CNN Accelerators. - Youngbeom Jung; Yeongjae Choi; Jaehyeong Sim; Lee-Sup Kim (ICCAD, 2019)

An Energy-efficient Processing-in-memory Architecture for Long Short Term Memory in Spin Orbit Torque MRAM. - Kyeonghan Kim; Hyein Shin; Jaehyeong Sim; Myeonggu Kang; Lee-Sup Kim (ICCAD, 2019)

A PVT-robust Customized 4T Embedded DRAM Cell Array for Accelerating Binary Neural Networks. - Hyein Shin; Jaehyeong Sim; Daewoong Lee; Lee-Sup Kim (ICCAD, 2019)

An Energy-Efficient Deep Convolutional Neural Network Training Accelerator for In Situ Personalization on Smart Devices. - Seungkyu Choi; Jaehyeong Sim; Myeonggu Kang; Yeongjae Choi; Hyeonuk Kim; Lee-Sup Kim (IEEE J. Solid State Circuits, 2020)

CREMON: Cryptography Embedded on the Convolutional Neural Network Accelerator. - Yeongjae Choi; Jaehyeong Sim; Lee-Sup Kim (IEEE Trans. Circuits Syst., 2020)

An Energy-Efficient Deep Convolutional Neural Network Inference Processor With Enhanced Output Stationary Dataflow in 65-nm CMOS. - Jaehyeong Sim; Somin Lee; Lee-Sup Kim (IEEE Trans. Very Large Scale Integr. Syst., 2020)

S-FLASH: A NAND Flash-Based Deep Neural Network Accelerator Exploiting Bit-Level Sparsity. - Myeonggu Kang; Hyeonuk Kim; Hyein Shin; Jaehyeong Sim; Kyeonghan Kim; Lee-Sup Kim (IEEE Trans. Computers, 2022)

Optimization of the Modified Gaussian Filter for Mobile GPU Usage in Game Workloads. - Jieui Kang; Jaehyeong Sim; Hyokyung Bahn (CCCI, 2023)

TD-NAAS: Template-Based Differentiable Neural Architecture Accelerator Search. - HaYoung Lim; Yeseo Jang; Juyeon Kim; Jaehyeong Sim (ISOCC, 2023)

AutoCaps-Zero: Searching for Hardware-Efficient Squash Function in Capsule Networks. - Jieui Kang; Sooyoung Kwon; Hyojin Kim; Jaehyeong Sim (CCCI, 2024)

OCW: Enhancing Few-Shot Learning with Optimized Class-Weighting Methods. - Jieui Kang; Subean Lee; Eunseo Kim; Soeun Choi; Jaehyeong Sim (CCCI, 2024)

An Energy-Efficient Hardware Accelerator for On-Device Inference of YOLOX. - Kyungmi Kim; Soeun Choi; Eunkyeol Hong; Yoonseo Jang; Jaehyeong Sim (ISOCC, 2024)

BS2: Bit-Serial Architecture Exploiting Weight Bit Sparsity for Efficient Deep Learning Acceleration. - Eunseo Kim; Subean Lee; Chaeyun Kim; HaYoung Lim; Jimin Nam; Jaehyeong Sim (ISOCC, 2024)

AlphaAccelerator: An Automatic Neural FPGA Accelerator Design Framework Based on GNNs. - Jiho Lee; Jieui Kang; Eunjin Lee; Yejin Lee 014; Jaehyeong Sim (ISOCC, 2024)

SpDRAM: Efficient In-DRAM Acceleration of Sparse Matrix-Vector Multiplication. - Jieui Kang; Soeun Choi; Eunjin Lee; Jaehyeong Sim (IEEE Access, 2024)

Q-LAtte: An Efficient and Versatile LSTM Model for Quantized Attention-Based Time Series Forecasting in Building Energy Applications. - Jieui Kang; Jihye Park; Soeun Choi; Jaehyeong Sim (IEEE Access, 2024)

Enhancing Gender Prediction Model Performance through Automatic Individual Entity Extraction and Class Balance. - Chaeyun Kim; Eunseo Kim; Yeonhee Kim; Jaehyeong Sim; Jongkil Kim (BigComp, 2025)

PRISM-Med: Parameter-Efficient Robust Interdomain Specialty Model for Medical Language Tasks. - Jieui Kang; Hyungon Ryu; Jaehyeong Sim (IEEE Access, 2025)