Geon-Woo Kim

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Thank you for visiting my website! I’m Geon-Woo Kim, a Ph.D. student at UT Austin, where I’m advised by Prof. Aditya Akella and Prof. Daehyeok Kim . I received my Bachelor’s degree from Seoul National University, where I was advised by Prof. Byung-Gon Chun. My research interests lie in systems for machine learning, with a recent focus on tackling the challenges of large-scale model training and inference. Prior to beginning my Ph.D. program, I had the pleasure of working as a software engineer at Viva Republica, a startup that operates one of South Korea’s largest fintech services.

Please see my cv for more details.

Email: gwkim [at] utexas [dot] edu

Linkedin Profile

Education

The University of Texas at Austin
  • Ph.D. in Computer Science, Nov 2026 (Expected)
  • M.S. in Computer Science, 2025
Seoul National University
  • B.S. in Computer Science & Engineering, Summa cum laude
  • B.S. in Mathematical Sciences (Double Major)

Publications

2026

  1. Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation
    Geon-Woo Kim, Donghyun Kim, Jeongyoon Moon, Henry Liu, Tarannum Khan, Anand Iyer, Daehyeok Kim, and Aditya Akella
    IEEE International Parallel and Distributed Processing Symposium (IPDPS 26)
    [Paper]
  2. Democratizing MoE LLM Decoding via Barrier-Free Expert Parallelism
    Yizhuo Liang, Shaoyu Wang, Jaeyong Song, Yanqi Zhou, Geon-Woo Kim, Guangrong He, and Seo Jin Park
    In The 32nd ACM Symposium on Operating Systems Principles (To Appear at SOSP ’26)
  3. Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
    Joon Ha Kim, Geon-Woo Kim, Anoop Rachakonda, and Daehyeok Kim
    preprint

2025

  1. HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
    Geon-Woo Kim, Junbo Li, Shashidhar Gandham, Omar Baldonado, Adithya Gangidi, Pavan Balaji, Zhangyang Wang, and Aditya Akella
    In Forty-second International Conference on Machine Learning (ICML 25)
    [Paper]
  2. StitchLLM: Serving LLMs, One Block at a Time
    Bodun Hu, Shuozhe Li, Saurabh Agarwal, Myungjin Lee, Akshay Jajoo, Jiamin Li, Le Xu, Geon-Woo Kim, Donghyun Kim, Hong Xu, Amy Zhang, and Aditya Akella
    The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 25)
    [Paper]

2024

  1. Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
    Ruisi Cai, Yeonju Ro, Geon-Woo Kim, Peihao Wang, Babak Ehteshami Bejnordi, Aditya Akella, and Zhangyang Wang
    In Advances in Neural Information Processing Systems (NeurIPS 24)
    [Paper]
  2. Lovelock: Towards Smart NIC-hosted Clusters
    Seo Jin Park, Ramesh Govindan, Kai Shen, David Culler, Fatma Özcan, Geon-Woo Kim, and Hank Levy
    In HotCarbon Workshop on Sustainable Computer Systems (HotCarbon 24)
    [Paper]

2022

  1. Orca: A Distributed Serving System for Transformer-Based Generative Models
    Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, and Byung-Gon Chun
    In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)
    [Paper]

2021

  1. Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs
    Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeongin Yu, and Byung-Gon Chun
    In Advances in Neural Information Processing Systems (NeurIPS 21)
    [Paper] [Supp]

2019

  1. Apache Nemo: A Framework for Building Distributed Dataflow Optimization Policies
    Youngseok Yang, Jeongyoon Eo, Geon-Woo Kim, Joo Yeon Kim, Sanha Lee, Jangho Seo, Won Wook Song, and Byung-Gon Chun
    In 2019 USENIX Annual Technical Conference (USENIX ATC 19)
    [Paper]

2017

  1. Pado: A Data Processing Engine for Harnessing Transient Resources in Datacenters
    Youngseok Yang, Geon-Woo Kim, Won Wook Song, Yunseong Lee, Andrew Chung, Zhengping Qian, Brian Cho, and Byung-Gon Chun
    In Proceedings of the Twelfth European Conference on Computer Systems (EuroSys 17)
    [Paper]