Contact
51 Prospect St, New Haven, CT 06511
Office: Room 207, Arthur K. Watson Hall
Email: in.gim@yale.edu
I am a third-year Ph.D. student in the Department of Computer Science at Yale University,
where I work with Prof. Lin Zhong in the Efficient Computing Lab.
My research is at the intersection of computer systems and AI.
Lately, I have been focusing on improving the reliability and efficiency of LLMs by making them programmable.
Before starting my Ph.D. program at Yale, I received my B.S. degree from Yonsei University in Korea in 2021.
Curriculum vitae. My name is 김인 in Hangul.
📌 I am actively looking for internship opportunities in the summer of 2025. Please feel free to reach out if you are interested in working with me.
Recent news
- 2024. 09. Our recent work on confidential LLM prompting is available on arXiv.
- 2024. 02. Prompt Cache is accepted to MLSys 2024!
- 2023. 10. Our recent work on LLM prompt caching has been uploaded to arXiv.
- 2022. 08. Starting my academic journey at Yale.
Publications
-
Confidential Prompting: Protecting User Prompts from Cloud LLM Providers
In Gim, Caihua Li, and Lin Zhong
September 2024 (preprint) -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
In Gim, Guojun Chen, Seung-Seob Lee, Nikhil Sarda, Anurag Khandelwal, and Lin Zhong
MLSys 2024, May 2024 (code, pdf) -
Memory-Efficient DNN Training on Mobile Devices
In Gim and JeongGil Ko
MobiSys 2022, July 2022 (code, pdf) -
Fast Monte-Carlo Approximation of the Attention Mechanism
Hyunjun Kim (In Gim) and JeongGil Ko
AAAI 2022, January 2022 (code, pdf)
Talks
- 2024. 09. LLM prompt caching
Invited talk at NVIDIA