| 2024 | ICCAD | FlexInt: A New Number Format for Robust Sub-8-Bit Neural Network Inference. | Minuk Hong, Hyeonuk Sim, Sugil Lee, Jongeun Lee |
| 2023 | DAC | NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM. | Jaewoo Park, Sugil Lee, Jongeun Lee |
| 2022 | ACSSC | Multi-Fidelity Nonideality Simulation and Evaluation Framework for Resistive Neuromorphic Computing. | Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Jongeun Lee |
| 2022 | ICCD | Accurate Prediction of ReRAM Crossbar Performance Under I-V Nonlinearity and IR Drop. | Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi |
| 2021 | CVPR | Automated Log-Scale Quantization for Low-Cost Deep Neural Networks. | Sangyun Oh, Hyeonuk Sim, Sugil Lee, Jongeun Lee |
| 2021 | DATE | Cost- and Dataset-free Stuck-at Fault Mitigation for ReRAM-based Deep Learning Accelerators. | Giju Jung, Mohammed E. Fouda, Sugil Lee, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi |
| 2021 | ICCD | Fast and Low-Cost Mitigation of ReRAM Variability for Deep Learning Applications. | Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi |
| 2020 | DAC | Learning to Predict IR Drop with Effective Training for ReRAM-based Neural Network Hardware. | Sugil Lee, Giju Jung, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi |
| 2019 | ASPDAC | On-chip memory optimization for high-level synthesis of multi-dimensional data on FPGA. | Daewoo Kim, Sugil Lee, Jongeun Lee |
| 2019 | DAC | Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing. | Sugil Lee, Hyeon Uk Sim, Jooyeon Choi, Jongeun Lee |
| 2018 | DAC | Sign-magnitude SC: getting 10X accuracy for free in stochastic computing for deep neural networks. | Aidyn Zhakatayev, Sugil Lee, Hyeon Uk Sim, Jongeun Lee |