Haiyun He

(Pronunciation: /ˈhaɪyuːŋ ˈhɜː/,   Pronouns: she/her/hers)
Postdoc Associate, Center for Applied Mathematics, Cornell University

prof_pic.jpg

(Taken at Cornell Slope)

Hi! I am currently a postdoc at Cornell University, working with Prof. Ziv Goldfeld from ECE and Prof. Christina Lee Yu from ORIE. I am honored to be funded by the Center for Applied Mathematics postdoctoral fellowship. Before joining Cornell, I obtained my PhD degree in Electrical and Computer Engineering from National University of Singapore in Sep. 2022, advised by Prof. Vincent Y. F. Tan.

My recent research interests lie in the intersection of information theory and machine learning, including but not limited to:

  • Machine learning and statistical learning theory
  • Hypothesis testing
  • Inference and estimation
  • Wireless communications

If you are interested in collaborating with me, please do not hesitate to drop me an email (at the bottom) or drop by  657 Rhodes Hall, Ithaca, NY  !

⭐ I am on the 2024-2025 academic job market. Please feel free to reach out!

News

03/06/2025 Attending 8th C^3 Workshop at University of Florida between Mar. 06-07, 2025. My talk “Distributional Information Embedding: A Framework for LLM Watermarking” is in the afternoon on Mar. 06. Thank Sean and Yuheng for their invitation! I am glad to visit the beautiful town Gainesville, see a big family of allegators :crocodile:, and meet new friends!
02/10/2025 Attending 2025 ITA Workshop at UCSD between Feb. 09-11, 2025. My talk is on Monday afternoon, Feb. 10. Glad to meet old and new friends!
09/09/2024 Going to attend Workshop II: Theory and Practice of Deep Learning at IPAM, UCLA between Oct. 14-18.

Recent publications

  1. Distributional Information Embedding: A Framework for Multi-bit Watermarking
    Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
    Submitted, Jan 2025
  2. Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
    Haiyun He*, Yepeng Liu*, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
    Submitted, Oct 2024
  3. Information-Theoretic Generalization Bounds for Deep Neural Networks
    Haiyun He, Christina Lee Yu, and Ziv Goldfeld
    Full-length version submitted, Apr 2024