Natural hdr image tone mapping based on retinex. - Kyungman Kim; Jonghyun Bae; Jaeseok Kim (IEEE Trans. Consumer Electron., 2011)

A new edge directed interpolation algorithm using accurate estimation of edge directional covariance. - Jonghyun Bae; Yujin Yun; Kyungman Kim; Jaeseok Kim (ISCAS, 2012)

Exploring the Role of a Smartphone as a Motion Sensing and Control Device in the Wireless Networked Control of a Motor Test-bed. - Jared Alan Frank; Anthony Brill; Jonghyun Bae; Vikram Kapila (ICINCO (2), 2015)

Jointly optimizing task granularity and concurrency for in-memory mapreduce frameworks. - Jonghyun Bae; Hakbeom Jang; Wenjing Jin 001; Jun Heo 001; Jaeyoung Jang; Joo Young Hwang; Sangyeun Cho; Jae W. Lee (IEEE BigData, 2017)

Practical Erase Suspension for Modern Low-latency SSDs. - Shine Kim; Jonghyun Bae; Hakbeom Jang; Wenjing Jin 001; Jeonghun Gong; SeungYeon Lee; Tae Jun Ham; Jae W. Lee (USENIX ATC, 2019)

Eager Memory Management for In-Memory Data Analytics. - Hakbeom Jang; Jonghyun Bae; Tae Jun Ham; Jae W. Lee (IEICE Trans. Inf. Syst., 2019)

SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning. - Jonghyun Bae; Hakbeom Jang; Jeonghun Gong; Wenjing Jin 001; Shine Kim; Jaeyoung Jang; Tae Jun Ham; Jinkyu Jeong; Jae W. Lee (IEEE Micro, 2019)

A Case for Hardware-Based Demand Paging. - Gyusun Lee; Wenjing Jin 001; Wonsuk Song; Jeonghun Gong; Jonghyun Bae; Tae Jun Ham; Jae W. Lee; Jinkyu Jeong (ISCA, 2020)

FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks. - Jonghyun Bae; Jongsung Lee 001; Yunho Jin; Sam Son; Shine Kim; Hakbeom Jang; Tae Jun Ham; Jae W. Lee (FAST, 2021)

Behemoth: A Flash-centric Training Accelerator for Extreme-scale DNNs. - Shine Kim; Yunho Jin; Gina Sohn; Jonghyun Bae; Tae Jun Ham; Jae W. Lee (FAST, 2021)

Layerweaver: Maximizing Resource Utilization of Neural Processing Units via Layer-Wise Scheduling. - Young H. Oh; Seonghak Kim; Yunho Jin; Sam Son; Jonghyun Bae; Jongsung Lee 001; Yeonhong Park; Dong Uk Kim; Tae Jun Ham; Jae W. Lee (HPCA, 2021)

A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction. - Zhengnan Huang; Jonghyun Bae; Patricia M. Johnson; Terlika Sood; Laura Heacock; Justin Fogarty; Linda Moy; Sungheon Gene Kim; Florian Knoll (MLMIR@MICCAI, 2021)

ASAP: Fast Mobile Application Switch via Adaptive Prepaging. - Sam Son; Seung Yul Lee; Yunho Jin; Jonghyun Bae; Jinkyu Jeong; Tae Jun Ham; Jae W. Lee; Hongil Yoon (USENIX ATC, 2021)

L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training. - Jonghyun Bae; Woohyeon Baek; Tae Jun Ham; Jae W. Lee (ECCV (11), 2022)

PyNET-QxQ: A Distilled PyNET for QxQ Bayer Pattern Demosaicing in CMOS Image Sensor. - Minhyeok Cho; Haechang Lee 001; Hyunwoo Je; Kijeong Kim; Dongil Ryu; Jinsu Kim; Jonghyun Bae; Albert No (CoRR, 2022)

Liquid: Mix-and-Match Multiple Image Formats to Balance DNN Training Pipeline. - Woohyeon Baek; Jonghyun Bae; Donghyun Lee 005; Hyunwoong Bae; Yeonhong Park; Jae W. Lee (APSys, 2023)

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets. - Jong Youl Choi; Massimiliano Lupo Pasini; Pei Zhang; Kshitij Mehta; Frank Liu 001; Jonghyun Bae; Khaled Ibrahim (SC Workshops, 2023)

Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function. - Jonghyun Bae; Chenyang Li 010; Arjun V. Masurkar; Yulin Ge; Sungheon Gene Kim (NeuroImage, 2023)

ISP2DLA: Automated Deep Learning Accelerator Design for On-Sensor Image Signal Processing. - Dong-eon Won; Yeeun Kim; Janghwan Lee; Minjae Lee; Jonghyun Bae; Jongjoo Park; Jeongyong Song; Jungwook Choi (ASAP, 2024)

MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural Networks Training. - Jonghyun Bae; Jong Youl Choi; Massimiliano Lupo Pasini; Kshitij Mehta; Khaled Z. Ibrahim (IPDPS (Workshops), 2024)

MDLoader: A Hybrid Model-Driven Data Loader for Distributed Graph Neural Network Training. - Jonghyun Bae; Jong Youl Choi; Massimiliano Lupo Pasini; Kshitij Mehta; Pei Zhang; Khaled Z. Ibrahim (SC Workshops, 2024)

Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jorda Polo; Prasanna Balaprakash (CoRR, 2024)

SkipLSM: Fast Retrieval of Hot Key-Value Pairs on LSM Tree. - Jongsung Lee 001; Sam Son; Jonghyun Bae; Yunho Jin; Tae Jun Ham; Jae W. Lee (SAC, 2025)

Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jordà Polo; Prasanna Balaprakash (J. Supercomput., 2025)