Donghyun Son

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I’m an incoming Master’s student in Computer Science at Stanford, working at the intersection of ML and systems. I’m particularly interested in algorithms that leverage the inherent sparsity in large models.

During my undergraduate studies, I was fortunate to work with outstanding advisors: Prof. Sungjoo Yoo from SNU, Prof. Buru Chang from Hyperconnect, Prof. Aditya Akella and Dr. Saurabh Agarwal from UT Austin.

I’m open to collaboration, so feel free to reach out.

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