Publications
[Google Scholar] [ORCID]
Conference Papers
GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation [paper] [arXiv]Â
Sungmin Kang, Jisoo Kim, Salman Avestimehr, Sunwoo Lee
AAAI, 2026
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning [paper] [arXiv]
Jisoo Kim, Sungmin Kang, Sunwoo Lee
NeurIPS, 2025
Enabling Weak Client Participation via On-Device Knowledge Distillation in Heterogeneous Federated Learning [paper] [arXiv]
Jihyun Lim, Junhyuk Jo, Tuo Zhang, Sunwoo Lee
ECAI, 2025
Layer-Wise Adaptive Gradient Norm Penalizing Method for Efficient and Accurate Deep Learning [paper] [arXiv]
Sunwoo Lee
KDD, 2024
Layer-wise Adaptive Model Aggregation for Scalable Federated Learning (Oral Presentation) [paper] [arXiv]
Sunwoo Lee, Tuo Zhang, Salman Avestimehr
AAAI, 2023
Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr
ICASSP, 2023
Using Multi-resolution Data to Accelerate Neural Network Training in Scientific Applications [paper]
Kewei Wang, Sunwoo Lee, Jan Balewski, Alex Sim, Peter Nugent, Ankit Agrawal, Alok Choudhary, Kesheng Wu, Wei-keng Liao
CCGrid, 2022
Supporting Data Compression in PnetCDF [paper]
Kaiyuan Hou, Qiao Kang, Sunwoo Lee, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
BigData, 2021
Asynchronous I/O Strategy for Large-Scale Deep Learning Applications [paper]
Sunwoo Lee, Qiao Kang, Kewei Wang, Jan Balewski, Alex Sim, Ankit Agrawal, Alok Choudhary, Peter Nugent, Kesheng Wu, Wei-keng Liao
HiPC, 2021
SIGRNN: Synthetic minority Instances Generation in imbalanced datasets using a Recurrent Neural Network [paper]
Reda Al-Bahrani, Dipendra Jha, Qiao Kang, Sunwoo Lee, Zijiang Yang, Wei-keng Liao, Ankit Agrawal, Alok Choudhary
ICPRAM, 2021
Communication-Efficient Local Stochastic Gradient Descent for Scalable Deep Learning [paper]
Sunwoo Lee, Qiao Kang, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
BigData, 2020
Improving All-to-Many Personalized Communication in Two-Phase I/O [paper]
Qiao Kang, Robert Ross, Robert Latham, Sunwoo Lee, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
SC, 2020
Predicting Resource Requirement in Intermediate Palomar Transient Factory Workflow [paper]
Qiao Kang, Alex Sim, Peter Nugent, Sunwoo Lee, Wei-keng Liao, Ankit Agrawal, Alok Choudhary, Kesheng Wu
CCGrid, 2020
Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time [paper]
Sunwoo Lee, Qiao Kang, Sandeep Madireddy, Prasanna Balaprakash, Ankit Agrawal, Alok Choudhary, Richard Archibald, Wei-keng Liao
BigData, 2019
Parallelizing Deep Convolutional Neural Network Training by Exploiting the Overlapping of Computation and Communication (Best Paper Finalist) [paper]
Sunwoo Lee, Dipendra Jha, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
HiPC, 2017
Parallel Community Detection Algorithm Using a Data Partitioning Strategy with Pairwise Subdomain Duplication [paper]
Diana Palsetia, William Hendrix, Sunwoo Lee, Ankit Agrawal, Wei-keng Liao, Alok Choudhary
ISC, 2016
Journals
Highly Stable Two-level Current Fluctuation in Complex Oxide Heterostructures [paper]
Doyeop Kim, Jung-Woo Lee, Jihyun Lim, Sungjun Choi, Khimananda Acharya, Seobin Oh, Jaewhan Oh, Tula R. Paudel, Yongsoo Yang, Kitae Eom, Sunwoo Lee, Hyungwoo Lee
Nature Communications, 2025
Machine Learning Approach to Characterize Ferromagnetic La0.7Sr0.3MnO3 Thin Films via Featurization of Surface Morphology [paper]
Sanghyeok Ryou, Jihyun Lim, Minwoo Jang, Kitae Eom, Sunwoo Lee, Hyungwoo Lee
Advanced Science, 2025
Embracing Federated Learning: Enabling Weak Client Participation via Partial Model Training [paper]
Sunwoo Lee, Tuo Zhang, Saurav Prakash, Yue Niu, Salman Avestimehr
IEEE Transactions on Mobile Computing, 2024
Overcoming Resource Constraints in Federated Learning: Large Models Can Be Trained with only Weak Clients [paper]
Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr
Transactions on Machine Learning Research, 2023
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization [arXiv]
Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr
Transactions on Machine Learning Research, 2023
Sunwoo Lee, Anit Sahu, Chaoyang He, Salman Avestimehr
Neurocomputing, 2023
Achieving Small-Batch Accuracy with Large-Batch Scalability via Hessian-Aware Learning Rate Adjustment [paper]
Sunwoo Lee, Chaoyang He, Salman Avestimehr
Neural Networks, 2023
Probing Oxygen Vacancy Distribution in Oxide Heterostructure by Deep Learning-based Spectral Analysis of Current Noise [paper]
Sunwoo Lee, Jaeyoung Jeon, Hyungwoo Lee
Applied Surface Science, 2022
Variance-aware weight quantization of multi-level resistive switching devices based on Pt/LaAlO3/SrTiO3 heterostructures [paper]
Sunwoo Lee, Jaeyoung Jeon, Kitae Eom, Chaehwa Jeong, Yongsoo Yang, Ji-Yong Park, Chang-Beom Eom, Hyungwoo Lee
Scientific Reports, 2022
Improving Scalability of Parallel CNN Training by Adaptively Adjusting Parameter Update Frequency [paper]
Sunwoo Lee, Qiao Kang, Reda Al-Bahrani, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
Journal of Parallel and Distributed Computing, 2022
A Case Study on Parallel HDF5 Dataset Concatenation for High-Energy Physics Data Analysis [paper] [arXiv]
Sunwoo Lee, Kai-yuan Hou, Kewei Wang, Saba Sehrish, Marc Paterno, James Kowalkowski, Quincey Koziol, Robert Ross, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
Parallel Computing, 2022
In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning [paper]
Sandeep Madireddy, Ji Hwan Park, Sunwoo Lee, Prasanna Balaprakash, Shinjae Yoo, Wei-keng Liao, Cory D Hauck, M Paul Laiu, Richard Archibald
Machine Learning: Science and Technology, 2020
Qiao Kang, Sunwoo Lee, Kai-yuan Hou, Robert Ross, Ankit Agrawal, Alok Choudhary, Wei-keng Liao
IEEE Transactions on Parallel and Distributed Systems, 2020
Workshop Papers
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training
Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr
CVPR workshop, 2025
Federated Learning of Large Model at the Edge via Principal Sub-Model Training
Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr
NeurIPS workshop, 2022
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
Sunwoo Lee, Anit Sahu, Chaoyang He, Salman Avestimehr
AAAI workshop, 2022
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision (Best Paper Award)
Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr
AAAI workshop, 2022
SLIM-QN: A Stochastic, Light, and Momentumized Quasi-Newton Optimizer for Deep Neural Networks
Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr
ICML workshop, 2021
Communication-Efficient Parallelization Strategy for Deep Convolutional Neural Network Training
Sunwoo Lee, Ankit Agrawal, Prasanna Balaprakash, Alok Choudhary, Wei-keng Liao
SC workshop, 2018
(Ph.D. thesis) Scalable Parallelization Strategy for Large-Scale Deep Learning, Sunwoo Lee, Ph.D. Thesis, Northwestern University, 2020
(M.S. thesis) Component-based Design and Performance Analysis for Multiprocessor Embedded Real-Time Software, Sunwoo Lee, M.S. Thesis, Hanyang University, 2009