Welcome :)

Hello, I am incoming Ph.D. student in Electrical Engineering Department at Yale University, under supervised by Prof. Priyadarshini Panda.

I received B.E. degree in Mechanical Engineering Department at Yonsei University, South Korea and M.S. degree in Precision Instrument at Tsinghua University, China. Prior to joining Yale, I worked as an AI researcher at Ulsan National Institute of Science and Technology (UNIST), South Korea. My research interests center around spiking neural network, efficient deep learning strategies, and neuromorphic computing.

News

2024

• [Jul] 📖 One paper is accepted to the 18th European Conference on Computer Vision (ECCV).
• [Apr] 📖 One paper is accepted to Applied Materials Today.
• [Feb] 🎉 I will be starting my Ph.D. in Electrical Engineering at Yale University from Fall 2024!
• [Feb] 📖 One paper is accepted to Advanced Functional Materials.
• [Jan] 📖 One paper is accepted to the 27th Design, Automation and Test in Europe Conference (DATE).

Publications

• Spiking Transformer with Spatial-Temporal Attention
  Donghyun Lee, Youngeun Kim, Yuhang Li, Shiting Xiao, Priyadarshini Panda
  Underivew

• Scaling Direct Feedback Alignment for ImageNet Training
  Yuhang Li, Ruokai Yin, Donghyun Lee, Youngeun Kim, Souvik Kundu, Priyadarshini Panda
  Underivew

• ReSpike: Residual Frames-based Spiking Neural Networks for Efficient Action Recognition
  Shiting Xiao, Yuhang Li, Youngeun Kim, Donghyun Lee, Priyadarshini Panda
  Underivew

• GenQ: Quantization in Low Data Regimes with Generative Synthetic Data
  Yuhang Li, Youngeun Kim, Donghyun Lee, Souvik Kundu, Priyadarshini Panda
  European Conference on Computer Vision (ECCV), 2024
  [paper]

• Forming-less flexible memristor crossbar array for neuromorphic computing applications produced using low-temperature atomic layer deposition
  Minjae Kim, Dong-eun Kim, Yue Wang, Donghyun Lee, Dong-Hyeok Lim, Haryeong Choi, Ioannis Kymissis, J Joshua Yang, Joonki Suh, Hong-Sub Lee, Hyung-Ho Park
  Applied Materials Today, 2024
  [paper]

• Molecularly Reconfigurable Neuroplasticity of Layered Artificial Synapse Electronics
  Dhananjay D Kumbhar, Yeonjin Je, Seongin Hong, Donghyun Lee, Hyeongtae Kim, Mi Ji Kwon, Su‐Yeon Cho, Do‐Hyeon Lee, Dong‐Hyeok Lim, Sunkook Kim, Jun Hong Park Advanced Functional Materials, 2024
  [paper]

• TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
  Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda Design, Automation and Test in Europe Conference (DATE), 2024
  [paper] [code]

• Wafer‐Scale Memristor Array Based on Aligned Grain Boundaries of 2D Molybdenum Ditelluride for Application to Artificial Synapses
  Jihoon Yang, Aram Yoon, Donghyun Lee, Seunguk Song, IL John Jung, Dong‐Hyeok Lim, Hongsik Jeong, Zonghoon Lee, Mario Lanza, Soon‐Yong Kwon
  Advanced Functional Materials, 2023
  [paper]

• Investigating Series and Parallel Oxide Memtransistors for Tunable Weight Update Properties
  Seung-Hyeon Kang, Seonguk Yang, Donghyun Lee, Sungkyu Kim, Joonki Suh, Hong-Sub Lee
  ACS Applied Electronic Materials, 2023
  [paper]

• Double-floating-gate van der Waals transistor for high-precision synaptic operations
  Hoyeon Cho, Donghyun Lee, Kyungmin Ko, Der-Yuh Lin, Huimin Lee, Sangwoo Park, Beomsung Park, Byung Chul Jang, Dong-Hyeok Lim, Joonki Suh
  ACS nano, 2023
  [paper]

• Filamentary and interface-type memristors based on tantalum oxide for energy-efficient neuromorphic hardware
  Minjae Kim, Malik Abdul Rehman, Donghyun Lee, Yue Wang, Dong-Hyeok Lim, Muhammad Farooq Khan, Haryeong Choi, Qing Yi Shao, Joonki Suh, Hong-Sub Lee, Hyung-Ho Park
  ACS applied materials & interfaces, 2022
  [paper]

• Policy gradient-based core placement optimization for multichip many-core systems
  Wooshik Myung, Donghyun Lee, Chenhang Song, Guanrui Wang, Cheng Ma
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
  [paper] [code]

• QTTNet: Quantized tensor train neural networks for 3D object and video recognition
  Donghyun Lee, Dingheng Wang, Yukuan Yang, Lei Deng, Guangshe Zhao, Guoqi Li
  Neural Networks, 2021
  [paper] [code]