Changwoo Lee
I am a fifth year Ph. D. student in the department of Electrical and Computer Engineering at the University of Michigan (U of M), advised by Prof. Hun-Seok Kim.
My research is centered around the efficient machine learning and deep learning models. Specifically, I am interested in the DNN Compression, learnable structural sparsity, and robust and efficient multi-modal systems.
Before I join U of M, I received my M.S. and B.S. at Hanyang University, Seoul, Republic of Korea.
news
Sep 25, 2024 | A paper “BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference” is accepted to NeurIPS24. |
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May 28, 2024 | I joined Samsung Research America at Mountain View as NLP/ML Research Intern during Summer 2024. |
Jan 16, 2024 | Paper on “Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks” is accepted to ICLR24. |
selected publications
- ISCA23TaskFusion: An Efficient Transfer Learning Architecture with Dual Delta Sparsity for Multi-Task Natural Language ProcessingIn Proceedings of the 50th Annual International Symposium on Computer Architecture 2023
- TCOMLearning-Based Near-Orthogonal Superposition Code for MIMO Short Message TransmissionIEEE Transactions on Communications 2023
- VLSIAudio and Image Cross-Modal Intelligence via a 10TOPS/W 22nm SoC with Back-Propagation and Dynamic Power GatingIn 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits) 2022