Haiyun He
(Pronunciation: /ˈhaɪyuːŋ ˈhɜː/, Pronouns: she/her/hers)
Assistant Professor, Internet of Things Thrust, HKUST(GZ)
(Taken at Cornell Slope)
Hi! I am currently an Assistant Professor in the Internet of Things (IoT) Thrust at the Hong Kong University of Science and Technology (Guangzhou). I am also a Cross-Campus Faculty Affiliate at HKUST. 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. Before joining HKUST(GZ), I was a postdoc in the Center for Applied Mathematics at Cornell University, working with Prof. Ziv Goldfeld from ECE and Prof. Christina Lee Yu from ORIE. I was honored to be funded by the Center for Applied Mathematics postdoctoral fellowship.
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
- Trustworthy AI
If you are interested in collaborating with me, please do not hesitate to drop me an email (at the bottom) or drop by my office W3-604 !
To apply, please send an email with your CV, transcript, and a brief statement of your research interests. Use the subject line:
[Year]-[PhD/Mphil/RA Application]-[Your Name], e.g., 25Fall-PhD Application-Haiyun He.
News
| 05/13/2026 |
 Congrats to my incoming PhD student Zhenxin Ai on his first watermarking paper accepted to ICML 2026, titled with “PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks”. He also made an excellent project page. Come to chat with him in Seoul!
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| 05/13/2026 |
Congrats to my PhD student Bingying Li on her first paper accepted to IEEE ISIT 2026, titled with “On the Generalization of Knowledge Distillation: An Information-Theoretic View”. See you in Guangzhou between Jun 28 and Jul 3.
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| 02/27/2026 |
We are organizing a workshop at ISIT 2026, ITGenNexus: Bridging Information Theory and Generative AI, including keynote talks, paper presentation, and panel discussion. We welcome up to 5-page workshop papers (non-archival) on various topics connecting Information Theory and Generative AI. Please find more details here.
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