| 2026 | DATE | LoRA-Edge: Tensor-Train-Assisted LoRA for Practical CNN Fine-Tuning on Edge Devices. | Hyunseok Kwak, Kyeongwon Lee, Jae-Jin Lee, Woojoo Lee |
| 2026 | DATE | TT-Edge: A Hardware-Software Co-Design for Energy-Efficient Tensor-Train Decomposition on Edge AI. | Hyunseok Kwak, Kyeongwon Lee, Kyeongpil Min, Chaebin Jung, Woojoo Lee |
| 2026 | ISLPED | Demo Abstract: An Energy-Efficient Crossbar-Free Oscillatory Neural Network Accelerator for Near-Sensor Edge AI. | Jeongmin Jin, Mundo Jeong, Kyeongwon Lee, Chaebin Jung, Eun-Su Cho, Woojoo Lee |
| 2026 | ISLPED | SA-Kura: An Energy-Efficient Systolic Array Accelerator for Locally-Coupled Kuramoto Drift in Diffusion Sampling. | Jeongmin Jin, Kyeongwon Lee, Mundo Jeong, Jongin Choi, Woojoo Lee |
| 2026 | ISLPED | CMAX-CAMEL: A Coarse-to-Fine Adaptive, Memory-Efficient, and Low-Power Edge Processor for Contrast Maximization. | Kyeongpil Min, Jongin Choi, Kyeongwon Lee, Woojoo Lee |
| 2025 | DAC | HH-PIM: Dynamic Optimization of Power and Performance with Heterogeneous-Hybrid PIM for Edge AI Devices. | Sangmin Jeon, Kangju Lee, Kyeongwon Lee, Woojoo Lee |
| 2025 | ISLPED | Demo Abstract: Radar-PIM-Lite: Ultra-Low-Power PIM Processor for Real-Time UWB Radar Respiration Detection on UAVs. | Kyeongwon Lee, Hyunseok Kwak, Kyeongpil Min, Chaebin Jung, Sangmin Jeon, Woojoo Lee, Jina Park, Massoud Pedram |