| 2026 | ASPDAC | Input Reuse, Weight-Stationary Dataflow and Mapping Strategy for Depthwise Convolution in Computing-in-Memory Neural Network Accelerators. | Chia-Chun Wang, Yu-Chih Tsai, Ren-Shuo Liu |
| 2026 | ISCAS | Adaptive Row-wise Attention Score Pruning and Compensation for Attention Acceleration. | Chia-Chun Wang, Yu-Lin Lin, Ren-Shuo Liu |
| 2026 | ISLPED | Tris-GCN: A 3D NAND Flash-based In-Storage Processing Architecture for GCN Acceleration. | Yi-Wa Wu, Jia-You Li, Chi-Jung Chen, Ching (Ryan) Cheng, Chia-Chun Wang, Chin-Fu Nien, Hsiang-Yun Cheng |
| 2025 | ICCD | Access Frequency-Aware Storage Reduction for Deep Learning Recommendation Model. | Chia-Chun Wang, Chuan-Yao Lai, Ren-Shuo Liu |
| 2023 | DATE | Built-in Self-Test and Built-in Self-Repair Strategies Without Golden Signature for Computing in Memory. | Yu-Chih Tsai, Wen-Chien Ting, Chia-Chun Wang, Chia-Cheng Chang, Ren-Shuo Liu |
| 2023 | ICCD | BICEP: Exploiting Bitline Inversion for Efficient Operation-Unit-Based Compute-in-Memory Architecture: No Retraining Needed! | Yun-Chen Lo, Chia-Chun Wang, Ren-Shuo Liu |
| 2023 | ICCD | CNN Inference Accelerators with Adjustable Feature Map Compression Ratios. | Yu-Chih Tsai, Chung-Yueh Liu, Chia-Chun Wang, Tsen-Wei Hsu, Ren-Shuo Liu |
| 2023 | ICCD | Exploiting and Enhancing Computation Latency Variability for High-Performance Time-Domain Computing-in-Memory Neural Network Accelerators. | Chia-Chun Wang, Yun-Chen Lo, Jun-Shen Wu, Yu-Chih Tsai, Chia-Cheng Chang, Tsen-Wei Hsu, Min-Wei Chu, Chuan-Yao Lai, Ren-Shuo Liu |
| 2022 | ICCAD | ISSA: Input-Skippable, Set-Associative Computing-in-Memory (SA-CIM) Architecture for Neural Network Accelerators. | Yun-Chen Lo, Chih-Chen Yeh, Jun-Shen Wu, Chia-Chun Wang, Yu-Chih Tsai, Wen-Chien Ting, Ren-Shuo Liu |