| 2026 | DATE | MD-SNN: Membrane Potential-aware Distillation on Quantized Spiking Neural Network. | Donghyun Lee, Abhishek Moitra, Youngeun Kim, Ruokai Yin, Priyadarshini Panda |
| 2025 | DAC | PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs. | Ruokai Yin, Yuhang Li, Priyadarshini Panda |
| 2025 | ICML | GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration. | Yuhang Li, Ruokai Yin, Donghyun Lee, Shiting Xiao, Priyadarshini Panda |
| 2025 | ISLPED | SITRA: Exploiting Temporal Silence in Spiking Transformers for Fast & Energy-efficient Inference. | Abhiroop Bhattacharjee, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda |
| 2024 | ASPDAC | MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks. | Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda |
| 2024 | DATE | TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. | Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda |
| 2024 | ICASSP | Are SNNs Truly Energy-efficient? - A Hardware Perspective. | Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda |
| 2024 | MICRO | LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks. | Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda |
| 2023 | ACSSC | Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract). | Abhishek Moitra, Ruokai Yin, Priyadarshini Panda |
| 2022 | ECCV | Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. | Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda |
| 2021 | ASPDAC | Normalized Stability: A Cross-Level Design Metric for Early Termination in Stochastic Computing. | Di Wu, Ruokai Yin, Joshua San Miguel |
| 2020 | ISCA | UGEMM: Unary Computing Architecture for GEMM Applications. | Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, Joshua San Miguel |