Ruokai Yin

PhD student, Electrical Engineering, Yale University

E-mail: ruokai.yin@yale.edu

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Bio

Ruokai is a second-year Computer Engineering PhD student in Department of Electrical Engineering at Yale University, advised by Prof. Priya Panda.

His research interests lie in designing low-power Computer Architectures for intelligent applications, in particular, Neural Networks. His current research focuses on improving the Energy Efficiency of Spiking Nerual Networks.

Prior to joining Yale, he recieved his BS-Electrical Engineering degree from the University of Wisconsin-Madison. During undergraduate time, He worked with Prof. Joshua San Miguel on computer architectures for stochastic computing.

Publication

MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks     [paper]   [code]
Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda

29th Asia and South Pacific Design Automation Conference (ASP-DAC), Jan, 2024


Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks     [paper]   [code]
Youngeun, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda

Frontiers in Neuroscience, 2023


Efficient Human Activity Recognition with Spatio-Temporal Spiking Neural Networks     [paper]   [code]
Yuhang Li, Ruokai Yin, Youngeun Kim, Priyadarshini Panda

Frontiers in Neuroscience, 2023


Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks     [paper]   [code]
Yuhang Li, Ruokai Yin, Hyoungseob Park, Youngeun Kim, Priyadarshini Panda

36th NeurIPS Workshop on Learning from Time Series for Health (Selected as Spotlight Paper), Dec, 2022


SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks     [paper]   [code]
Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022


Exploring Lottery Ticket Hypothesis in Spiking Neural Networks     [paper]   [code]
Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda

18th European Conference on Computer Vision (ECCV), Oct, 2022


uGEMM: Unary Computing for GEMM Applications     [paper]   [code]
Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, and Joshua San Miguel

IEEE Micro Top Picks, 2021


Normalized Stability: A Cross-Level Design Metric for Early Termination in Stochastic Computing     [paper]   [code]
Di Wu, Ruokai Yin, and Joshua San Miguel

Proceedings of the 26th Asia and South Pacific Design Automation Conference (ASPDAC), Jan, 2021


In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing     [paper]   [code]
Di Wu, Ruokai Yin, and Joshua San Miguel

IEEE Design & Test, 2021


uGEMM: Unary Computing Architecture for GEMM Applications     [paper]   [code]
Di Wu, Jingjie Li, Ruokai Yin, Hsuan Hsiao, Younghyun Kim, and Joshua San Miguel

47th Annual International Symposium on Computer Architecture (ISCA), Jun, 2020


Experience

July 2021-Present

Graduate Research Assistant, Intelligent Computing Lab
Yale University

Pursuing PhD degree with Prof. Priya Panda. Working on projects that improving the energy efficiency of neural networks, in particular, spiking neural networks.

June 2019-May 2021

Undergraduate Research Assistant, STACS Lab
University of Wisconsin-Madison

Advised by Prof. Joshua San Miguel. Worked on projects that applying unary computing to the deep neural networks. Construted a PyTorch-basede library for unary computing.

Teaching

2023 Fall

Teaching Fellow, EENG 439 Neural Networks and Learning Systems
Yale University

Instructor: Prof. Priya Panda. Course Description.

2023 Spring

Teaching Fellow, EENG 348/CPSC 338: Digital Systems
Yale University

Instructor: Prof. Rajit Manohar. Course Description.