Haiyang Huang

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I’m a final-year Ph.D. student in the Department of Computer Science at Duke University, under supervision of Prof. Cynthia Rudin and Prof. Benjamin C. Lee. I’m interested in improving transparency and efficiency of current machine learning models. Prior to joining Duke, I received my Bachelor’s degree in Mathematics and Computer Science from the University of Michigan, where I worked with Prof. Jenna Wiens.

You can reach me at hyhuang at cs dot duke dot edu.

Last Updated: November 2024.

news

Nov 10, 2024 Two of my papers are accepted at NeurIPS 2024. See you in Vancouver!
May 06, 2022 I am thrilled to join Facebook AI Research (FAIR) as a research intern starting at the middle of May!

latest posts

selected publications

  1. Toward Efficient Inference for Mixture of Experts
    Haiyang Huang, Newsha Ardalani , Anna Sun , and 5 more authors
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems , 2024
  2. Navigating the Effect of Parametrization for Dimensionality Reduction
    Haiyang Huang, Yingfan Wang , and Cynthia Rudin
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems , 2024
  3. Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
    Haiyang Huang, Newsha Ardalani , Anna Sun , and 6 more authors
    arXiv preprint arXiv:2303.06182, 2023
  4. SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation
    Haiyang Huang, Zhi Chen , and Cynthia Rudin
    arXiv preprint arXiv:2204.10926, 2022
  5. Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization
    Yingfan Wang , Haiyang Huang, Cynthia Rudin , and 1 more author
    Journal of Machine Learning Research, 2021
  6. Interpretable machine learning: Fundamental principles and 10 grand challenges
    Cynthia Rudin , Chaofan Chen , Zhi Chen , and 3 more authors
    Statistics Surveys, 2022