Doodle of a person fishing in a boat

Minchul Kang

Ph.D. Student, Computer Science, Korea University

I work on AI infrastructure, AI-based system optimizations, and GPU workload profiling and analysis.


Papers

* first author

  1. 1

    Parallelism Strategy Chaining for Fast Training Convergence

    Minchul Kang, Changyong Shin, Younghun Go, Hyunho Lee, Jinwoo Jeong, Chuck Yoo, Gyeongsik Yang

    EMNLP'26 Main (acceptance rate: 15.4%)
  2. 2

    GeoMesh: Workload-Balanced and Sign-Compressed Geo-Distributed LLM Training

    Changyong Shin, Jaerim Park, Minchul Kang, Younghun Go, Zhixiong Niu, Yongqiang Xiong, Gyeongsik Yang, Chuck Yoo

    EMNLP'26 Findings
  3. 3

    Unified KV Pooling to Accelerate Long-Context LLM Serving

    Minchul Kang, Changyong Shin, Jinwoo Jeong, Jaerim Park, Woohyun Kim, Bonyul Gu, Dongwoo Kang, Gyeongsik Yang, Chuck Yoo

    Preprint'26
  4. 4

    Making Sense of Job Preemption for Distributed Deep Learning Acceleration

    Younghun Go, Changyong Shin, Minchul Kang, Jae Hyun Hwang, Chuck Yoo, Gyeongsik Yang

    DAC'26
  5. 5

    GPU Memory Prediction for Multimodal Model Training

    Jinwoo Jeong, Minchul Kang (co-first author), Younghun Go, Changyong Shin, Hyunho Lee, Junho Yoon, Gyeongsik Yang, Chuck Yoo

    SAA '25 @ SOSP 2025
  6. 6

    Training Time Prediction for Mixed Precision-based Distributed Training

    Minchul Kang

    Preprint'26

Open Source

Books