Sangjin Choi

Sangjin Choi

Postdoctoral Researcher, Information & Electronics Research Institute, KAIST

I am a postdoctoral researcher in the CASYS Lab at KAIST's Information & Electronics Research Institute. I build cost-driven AI infrastructure with a deep understanding of hardware, systems software, and AI workloads.

During my Ph.D., I was advised by Prof. Youngjin Kwon and received additional mentorship from Prof. Jeongseob Ahn and Prof. Myeongjae Jeon. I have also worked closely with Yifan Xiong and Ziyue Yang at Microsoft Research Asia.

MoE Serving PD Disaggregation Energy-Efficient ML GPU Memory Management

News

Education

Work Experience

Publications

arXiv '26
ELDR: Expert-Locality-Aware Decode Routing for PD-Disaggregated MoE Serving
Sangjin Choi, Sukmin Cho, Yifan Xiong, Ziyue Yang, Youngjin Kwon, Peng Cheng
MLSys '26
BEAM: Joint Resource–Power Optimization for Energy-Efficient LLM Inference under SLO Constraints
Hyunjae Lee, Sangjin Choi, Seungjae Lim, Youngjin Kwon
EuroSys '26
MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud
Changjun Lee, Sangjin Choi, Youngjin Kwon
Findings of NAACL '25
Lossless Acceleration of Large Language Models with Hierarchical Drafting based on Temporal Locality in Speculative Decoding
Sukmin Cho, Sangjin Choi, Taeho Hwang, Jeongyeon Seo, Soyeong Jeong, Huije Lee, Hoyun Song, Jong C. Park, Youngjin Kwon
ICCAD '23
PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads
Jaehoon Heo, Yongwon Shin, Sangjin Choi, Sungwoong Yune, Jung-Hoon Kim, Hyojin Sung, Youngjin Kwon, Joo-Young Kim
USENIX ATC '23
EnvPipe: Performance-preserving DNN Training Framework for Saving Energy
Sangjin Choi, Inhoe Koo, Jeongseob Ahn, Myeongjae Jeon, Youngjin Kwon
USENIX ATC '22
Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory
Sangjin Choi*, Taeksoo Kim*, Jinwoo Jeong, Rachata Ausavarungnirun, Myeongjae Jeon, Youngjin Kwon, Jeongseob Ahn (*equal contribution)