Haonan Shi
503 Olin, 2001–2017 Martin Luther King Jr Dr
Cleveland, OH 44106
United States
I am a third-year Ph.D. candidate at Case Western Reserve University, advised by Prof. An Wang and co-advised by Dr. Tu Ouyang. My research focuses on Large Language Model Safety and Machine Learning Privacy. Prior to this, I received my bachelor’s degree from South China University of Technology, where I conducted research on privacy under the supervision of Prof. Hongyun Xu.
I am passionate about applying my research to real-world problems and look forward to internship opportunities and research collaborations.
Email: haonan.shi3[AT]case.edu(please replace “[AT]” by “@”)
research interests
My research lies at the intersection of Large Language Model Safety and Machine Learning Privacy. Specifically, the focus areas include:
Large Language Model Safety:
- Exploring post-training alignment for adaptive safety reasoning in LLMs, defending against jailbreaks while preserving inference efficiency and performance [AAAI].
Machine Learning Privacy:
news
| Nov 14, 2025 | 🎉 Our AAAI 2026 paper EASE: Practical and Efficient Safety Alignment for Small Language Models has been selected as an ORAL presentation! |
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| Nov 08, 2025 | Our paper titled EASE: Practical and Efficient Safety Alignment for Small Language Models was accepted by AAAI 2026. |
| May 21, 2025 | Our paper titled Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation was accepted by PoPETs 2025. |
| Mar 05, 2025 | Our paper titled Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models will also be a presentation at the ICLR25 FM-Wild workshop. |
| Jan 20, 2025 | Our paper titled Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models was accepted by WWW 2025. |
| Mar 26, 2024 | Our paper titled Learning-Based Difficulty Calibration for Enhanced Membership Inference Attacks was accepted by EuroS&P 2024. |
