| 2019 | HPCA | NAND-Net: Minimizing Computational Complexity of In-Memory Processing for Binary Neural Networks. | Hyeonuk Kim, Jaehyeong Sim, Yeongjae Choi, Lee-Sup Kim |
| 2019 | ICCAD | eSRCNN: A Framework for Optimizing Super-Resolution Tasks on Diverse Embedded CNN Accelerators. | Youngbeom Jung, Yeongjae Choi, Jaehyeong Sim, Lee-Sup Kim |
| 2019 | ICCAD | 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 |
| 2019 | ICCAD | A PVT-robust Customized 4T Embedded DRAM Cell Array for Accelerating Binary Neural Networks. | Hyein Shin, Jaehyeong Sim, Daewoong Lee, Lee-Sup Kim |
| 2018 | ICCAD | NID: processing binary convolutional neural network in commodity DRAM. | Jaehyeong Sim, Hoseok Seol, Lee-Sup Kim |
| 2018 | ISLPED | TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training. | Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Lee-Sup Kim |
| 2017 | DAC | A Kernel Decomposition Architecture for Binary-weight Convolutional Neural Networks. | Hyeonuk Kim, Jaehyeong Sim, Yeongjae Choi, Lee-Sup Kim |
| 2017 | ISLPED | SENIN: An energy-efficient sparse neuromorphic system with on-chip learning. | Myung-Hoon Choi, Seungkyu Choi, Jaehyeong Sim, Lee-Sup Kim |
| 2014 | ICCD | Timing error masking by exploiting operand value locality in SIMD architecture. | Jaehyeong Sim, Jun-Seok Park, Seungwook Paek, Lee-Sup Kim |
| 2012 | DAC | 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 |