Deferred Dropout: An Algorithm-Hardware Co-Design DNN Training Method Provisioning Consistent High Activation Sparsity. - Kangkyu Park; Yunki Han; Lee-Sup Kim (ICCAD, 2021)

EGCN: An Efficient GCN Accelerator for Minimizing Off-Chip Memory Access. - Yunki Han; Kangkyu Park; Youngbeom Jung; Lee-Sup Kim (IEEE Trans. Computers, 2022)

OptimStore: In-Storage Optimization of Large Scale DNNs with On-Die Processing. - Junkyum Kim; Myeonggu Kang; Yunki Han; Yanggon Kim; Lee-Sup Kim (HPCA, 2023)

Token-Picker: Accelerating Attention in Text Generation with Minimized Memory Transfer via Probability Estimation. - Junyoung Park; Myeonggu Kang; Yunki Han; Yanggon Kim; Jaekang Shin; Lee-Sup Kim (DAC, 2024)

CoCoA: Algorithm-Hardware Co-Design for Large-Scale GNN Training using Compressed Graph. - Yunki Han; Jaekang Shin; Gunhee Park; Lee-Sup Kim (ICCAD, 2024)

Accelerating Deep Reinforcement Learning via Phase-Level Parallelism for Robotics Applications. - Yanggon Kim; Yunki Han; Jaekang Shin; Junkyum Kim; Lee-Sup Kim (IEEE Comput. Archit. Lett., 2024)

EOD: Enabling Low Latency GNN Inference via Near-Memory Concatenate Aggregation. - Taehwan Kim; Yunki Han; Seohye Ha; Jiwan Kim; Lee-Sup Kim (ISCA, 2025)

AToM: Adaptive Token Merging for Efficient Acceleration of Vision Transformer. - Jaekang Shin; Myeonggu Kang; Yunki Han; Junyoung Park; Lee-Sup Kim (IEEE Trans. Computers, 2025)