Donghyun Son

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I’m currently looking for Ph.D. opportunities that are aligned with my interests. Feel free to reach me!

I am an undergraduate student majoring in Computer Science and Engineering at Seoul National University, currently studying abroad as an exchange student at UT Austin. Here, I am fortunate to work with Saurabh Agarwal on building efficient agentic systems, advised by Aditya Akella.

I aim to build an intelligent system that delivers strong problem-solving capabilities at low-cost. To pursue this goal, my research focuses on two directions: lowering the inference cost of large models, and improving training efficiency. My current interests include:

  • efficient long-context inference
  • data- and compute-efficient training of large models
  • system-level optimization of ML workloads

Aside from research, I enjoy algorithmic problem solving and have competed in competitive programming contests. You can find me on codeforces and BOJ.

Links: Github / CV / Google Scholar / X

 

Selected Publications

  1. NeurIPS 2025
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    NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache
    Donghyun Son, Euntae Choi, and Sungjoo Yoo
    In Advances in Neural Information Processing Systems (NeurIPS), 2025
    arXiv
  2. WSDM 2023 (Oral)
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    Reliable decision from multiple subtasks through threshold optimization: Content moderation in the wild
    Donghyun Son*, Byounggyu Lew*, Kwanghee Choi, and 5 more authors
    In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023
    arXiv
  3. OOD-CV@ICCV23
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    Gradient estimation for unseen domain risk minimization with pre-trained models
    Byounggyu Lew*, Donghyun Son*, and Buru Chang
    In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    arXiv