« Back to List Secure AI Inference Techniques: A Tutorial
Time / Place:
⏱️ 09/28 (Sat.) 09:30-11:15 at R0 - International Conference Hall
Abstract:
The intersection of LLM and privacy-preserving techniques is an emerging research field, particularly relevant for domain-specific applications. There is increasing interest in methodologies that enable collaborative or multi-tenant training and inference while addressing both trust and efficiency concerns. In this talk, I will give a high-level tutorial on several cryptographic techniques that may help the audience better understand the state-of-the-art research in the area of secure AI inference.
Biography:
- 鄭振牟 Chen-Mou Cheng
- Chang Gung University / Professor, Department of Artificial Intelligence
- Chen-Mou Cheng received his B.S. and M.S. degrees in electrical engineering from National Taiwan University in 1996 and 1998, respectively, as well as his PhD in computer science from Harvard University in 2007. He is currently a Professor at the Department of Artificial Intelligence, Chang Gung University. Between 2022 and 2024, he was the Chief Cryptographer at BTQ Technologies, Inc., a publicly-listed Canadian startup focusing on building post-quantum cryptographic technologies and solutions for blockchain applications. Between 2007 and 2022, he taught cryptography at National Taiwan University, Osaka University, and Kanazawa University.
- Co-panelists:
李育杰 Yuh-Jye Lee, 侯宜秀