Biography
I am Yeqi Huang, a PhD student specializing in AI-System at the Edinburgh-AISys Group. My research centers on enhancing system capabilities to support large-scale AI applications, encompassing training and inference processes. I enjoy engaging with various AI projects. However, AI nowadays are still not strong enough. My objective is to enhance the accessibility of AI for all individuals and to imbue AI with substantial utility in practical industrial applications.
This ambitious objective necessitates a methodical approach for its attainment. My prior research has centered on issues within High Performance Computing. So, I know well about the cutting edge problems in real sience and industry. To introduce AI into those field, we need serving larger AI models and we need to improve the performance of AI model's training and inference. In an attempt to address this issue, I endeavored to approach it from a more granular perspective by focusing on enhancing the system and compiler infrastructure. My recent research has centered on the latest generation of 2D Mesh Architecutre AI chips such as TPU and Cerebras.
BTW, I am an open-source developer. I love playing in Hackathons and shring my ideas on Github. And this is my blog: Personl Blog
Skills
TECHNICAL
HOBBIES
Interests
- Computer System
- Distributed Machine Learning
- Serverless System
Education
University of Edinburgh
University of Science and Technology of China
Recent Publications
RAGBoost: Efficient Retrieval-Augmented Generation with Accuracy-Preserving Context Reuse
Submitted to 8th Conference on Machine Learning and Systems (MLSys 2026) MLSys 2026 (Under Review)
WaferLLM: Large Language Model Inference at Wafer Scale
17th USENIX Symposium on Operating Systems Design and Implementation (OSDI 25) OSDI 2025
MoE-CAP: Benchmarking Cost, Accuracy and Performance of Sparse Mixture-of-Experts Systems
arXiv preprint arXiv
Projects
BTMR-Paper
Insanely Fast Paper Reading Tool - An AI-powered web application for extracting, analyzing, and summarizing academic papers
Bili-Investigate
A Streamlit-based web application for tracking Bilibili content creators' video updates with smart incremental fetching
YA-PapersWithCode
Yet Another Papers With Code - A modern recreation of the Papers With Code platform with AI-powered semantic search
ContextKeeper
AI assistant for RTX GPU users with extensible plugin ecosystem - A community fork of NVIDIA G-Assist
Contact
yeqi.huang@ed.ac.uk
10 Crichton Street, Edinburgh, United Kingdom
Informatics Forum Room 1.43
If you wanna discuss with me, use this tool: Schedule a meeting