Scaling Up IoT Stream Processing. - Taegeon Um; Gyewon Lee; Sanha Lee; Kyungtae Kim; Byung-Gon Chun (APSys, 2017)

Apache REEF: Retainable Evaluator Execution Framework. - Byung-Gon Chun; Tyson Condie; Yingda Chen; Brian Cho; Andrew Chung; Carlo Curino; Chris Douglas; Matteo Interlandi; Beomyeol Jeon; Joo Seong Jeong; Gyewon Lee; Yunseong Lee; et al. (ACM Trans. Comput. Syst., 2017)

High-Performance Stateful Stream Processing on Solid-State Drives. - Gyewon Lee; Jeongyoon Eo; Jangho Seo; Taegeon Um; Byung-Gon Chun (APSys, 2018)

Apache Nemo: A Framework for Optimizing Distributed Data Processing. - Won Wook Song; Youngseok Yang; Jeongyoon Eo; Jangho Seo; Joo Yeon Kim; Sanha Lee; Gyewon Lee; Taegeon Um; Haeyoon Cho 001; Byung-Gon Chun (ACM Trans. Comput. Syst., 2020)

Pluto: High-Performance IoT-Aware Stream Processing. - Taegeon Um; Gyewon Lee; 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)

FlowKV: A Semantic-Aware Store for Large-Scale State Management of Stream Processing Engines. - Gyewon Lee; Jaewoo Maeng; Jinsol Park; Jangho Seo; Haeyoon Cho 001; Youngseok Yang; Taegeon Um; Jongsung Lee 001; Jae W. Lee; Byung-Gon Chun (EuroSys, 2023)

Sponge: Fast Reactive Scaling for Stream Processing with Serverless Frameworks. - Won Wook Song; Taegeon Um; Sameh Elnikety; Myeongjae Jeon; Byung-Gon Chun (USENIX ATC, 2023)

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)

Blaze: Holistic Caching for Iterative Data Processing. - Won Wook Song; Jeongyoon Eo; Taegeon Um; Myeongjae Jeon; Byung-Gon Chun (EuroSys, 2024)

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)