Mideum_

Education

• Graduate: M.S. in Computer Science and Engineering
  Sogang University — 2023.02 – 2025.02
• Graduate: B.S. in Computer Science and Engineering (Double Major in Mathematics)
  Sogang University — 2019.03 – 2023.02

Career

• Runtime SW Engineer
  Dnotitia — 2025.04 – Present

Publications

• MemoryBridge: Leveraging Cloud Resource Characteristics for Cost-Efficient Disk-based GNN Training via Two-Level Architecture
  Yoochan Kim, Hong-Yeon Kim, Weikuan Yu, Youngjae Kim
  In proceedings of 2025 IEEE 25th International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (May 2025) [accepted for publication] [paper]
• Leveraging Pre-Built Catalogs and Object-Level Scheduling to Eliminate I/O Bottlenecks
  Seoyeong Lee, Junghwan Park, Yoochan Kim, Safdar Jamil, Awais Khan, Seung Woo Son, Jae-Kook Lee, Do-Sik An, Taeyoung Hong, Youngjae Kim
  IEEE Access (2025)
• Fault-Tolerant Deep Learning Cache with Hash Ring for Load Balancing in HPC Systems
  Seoyeong Lee, Awais Khan, Yoochan Kim, Junghwan Park, Soon Hwang, Jae-Kook Lee, Taeyoung Hong, Christopher Zimmer, Youngjae Kim
  In proceedings of SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis (2024) [paper]
• DeepVM: Integrating Spot and On-Demand VMs for Cost-Efficient Deep Learning Clusters in the Cloud
  Yoochan Kim, Kihyun Kim, Yonghyeon Cho, Jinwoo Kim, Awais Khan, Ki-Dong Kang, Baik-Song An, Myung-Hoon Cha, Hong-Yeon Kim, Youngjae Kim
  In proceedings of 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (May 2024) [paper]
• Optimizing Multi-level Checkpointing for Distributed Deep Learning Workloads on Cloud Spot VM Clusters
  Yonghyeon Cho, Yoochan Kim, Kihyun Kim, Jinwoo Kim, Hong-Yeon Kim, Youngjae Kim
  IEEE Access (2024) [paper]

Interests

• Cloud Systems
• Deep Learning I/O Optimization
• Mathematical Modeling
• Storage Systems
• Operating Systems

Skills

• C++
• Rust
• Python

Links

Email GitHub