Elastic Memory: Bring Elasticity Back to In-Memory Big Data Analytics. - Joo Seong Jeong; Woo-Yeon Lee; Yunseong Lee; Youngseok Yang; Brian Cho; Byung-Gon Chun (HotOS, 2015)

Automating System Configuration of Distributed Machine Learning. - Woo-Yeon Lee; Markus Weimer; Brian Cho; Byung-Gon Chun; Yunseong Lee; Joo Seong Jeong; Gyeong-In Yu; Jooyeon Kim; Hojin Park; Beomyeol Jeon; Won Wook Song; Gunhee Kim (ICDCS, 2019)

Lineage Checkpoint Approach for Long-lineage Problem in Apache Spark. - Minhyeok Kweun; Woo-Yeon Lee; Goeun Kim; Jisoo Hwang; Yoonkyong Lee (IEEE BigData, 2020)

Harmony: A Scheduling Framework Optimized for Multiple Distributed Machine Learning Jobs. - Woo-Yeon Lee; Yunseong Lee; Won Wook Song; Youngseok Yang; Jooyeon Kim; Byung-Gon Chun (ICDCS, 2021)

PokéMem: Taming Wild Memory Consumers in Apache Spark. - Minhyeok Kweun; Goeun Kim; Byungsoo Oh; Seongho Jung; Taegeon Um; Woo-Yeon Lee (IPDPS, 2022)

FastFlow: Accelerating Deep Learning Model Training with Smart Offloading of Input Data Pipeline. - Taegeon Um; Byungsoo Oh; Byeongchan Seo; Minhyeok Kweun; Goeun Kim; Woo-Yeon Lee (Proc. VLDB Endow., 2023)

Metis: Fast Automatic Distributed Training on Heterogeneous GPUs. - Taegeon Um; Byungsoo Oh; Minyoung Kang; Woo-Yeon Lee; Goeun Kim; Dongseob Kim; Youngtaek Kim; Mohd Muzzammil; Myeongjae Jeon (USENIX ATC, 2024)