Summary
Youngjae Kim is a professor of Computer Science and Engineering at Sogang University and a systems researcher with deep expertise in storage, I/O, and infrastructure-aware AI for data-intensive workloads. He combines academic leadership and industry collaboration—having led NVM research at Oak Ridge National Laboratory and served as a visiting researcher at SK Hynix—to push cross-layer designs for HPC, next-generation key-value stores, and SSD-aware OS/file-system support. His recent work optimizes LLM inference pipelines, RAG-based agentic systems, and high-capacity QLC/PLC SSD performance for cloud and on-prem deployments. With a Ph.D. from Penn State, over 100 publications, and a career spanning power/thermal modeling to flash translation layers, he brings both hands-on device-level insight and system-wide optimization skills. An interesting through-line in his career is translating low-level storage innovations into practical improvements for large-scale AI and HPC workflows.
9 years of coding experience