UGEMM: Unary Computing Architecture for GEMM Applications. - Di Wu 016; Jingjie Li; Ruokai Yin; Hsuan Hsiao; Younghyun Kim 001; Joshua San Miguel (ISCA, 2020)

Normalized Stability: A Cross-Level Design Metric for Early Termination in Stochastic Computing. - Di Wu 016; Ruokai Yin; Joshua San Miguel (ASP-DAC, 2021)

In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing. - Di Wu 016; Ruokai Yin; Joshua San Miguel (IEEE Des. Test, 2021)

uGEMM: Unary Computing for GEMM Applications. - Di Wu 016; Jingjie Li; Ruokai Yin; Hsuan Hsiao; Younghyun Kim 001; Joshua San Miguel (IEEE Micro, 2021)

Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. - Youngeun Kim; Yuhang Li 001; Hyoungseob Park; Yeshwanth Venkatesha; Ruokai Yin; Priyadarshini Panda (ECCV (12), 2022)

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks. - Yuhang Li 001; Ruokai Yin; Hyoungseob Park; Youngeun Kim; Priyadarshini Panda (CoRR, 2022)

Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract). - Abhishek Moitra; Ruokai Yin; Priyadarshini Panda (ACSSC, 2023)

Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing. - Abhishek Moitra; Ruokai Yin; Priyadarshini Panda (ACM Great Lakes Symposium on VLSI, 2023)

MINT: Multiplier-less Integer Quantization for Spiking Neural Networks. - Ruokai Yin; Yuhang Li 001; Abhishek Moitra; Priyadarshini Panda (CoRR, 2023)

Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks. - Youngeun Kim; Yuhang Li 001; Abhishek Moitra; Ruokai Yin; Priyadarshini Panda (CoRR, 2023)

SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. - Ruokai Yin; Abhishek Moitra; Abhiroop Bhattacharjee; Youngeun Kim; Priyadarshini Panda (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks. - Ruokai Yin; Yuhang Li 001; Abhishek Moitra; Priyadarshini Panda (ASPDAC, 2024)

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. - Donghyun Lee 002; Ruokai Yin; Youngeun Kim; Abhishek Moitra; Yuhang Li 001; Priyadarshini Panda (DATE, 2024)

Are SNNs Truly Energy-efficient? - A Hardware Perspective. - Abhiroop Bhattacharjee; Ruokai Yin; Abhishek Moitra; Priyadarshini Panda (ICASSP, 2024)

LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks. - Ruokai Yin; Youngeun Kim; Di Wu 016; Priyadarshini Panda (MICRO, 2024)

LoAS: Fully Temporal-Parallel Datatflow for Dual-Sparse Spiking Neural Networks. - Ruokai Yin; Youngeun Kim; Di Wu 016; Priyadarshini Panda (CoRR, 2024)

Do we really need a large number of visual prompts? - Youngeun Kim; Yuhang Li 001; Abhishek Moitra; Ruokai Yin; Priyadarshini Panda (Neural Networks, 2024)

Workload-Balanced Pruning for Sparse Spiking Neural Networks. - Ruokai Yin; Youngeun Kim; Yuhang Li 001; Abhishek Moitra; Nitin Satpute; Anna Hambitzer; Priyadarshini Panda (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs. - Ruokai Yin; Yuhang Li 001; Priyadarshini Panda (CoRR, 2025)

GPTQv2: Efficient Finetuning-Free Quantization for Asymmetric Calibration. - Yuhang Li 001; Ruokai Yin; Donghyun Lee 002; Shiting Xiao; Priyadarshini Panda (CoRR, 2025)

Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba. - Donghyun Lee 002; Yuhang Li 001; Ruokai Yin; Shiting Xiao; Priyadarshini Panda (CoRR, 2025)

DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs. - Ruokai Yin; Yuhang Li 001; Donghyun Lee 002; Priyadarshini Panda (CoRR, 2025)

DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration. - Arkapravo Ghosh; Abhishek Moitra; Abhiroop Bhattacharjee; Ruokai Yin; Priyadarshini Panda (CoRR, 2025)