School of Mathematics and Statistics Xi'an Jiaotong University
Hi, I am Jiaxuan Zou (邹嘉轩).
I am an undergraduate student in Mathematics and Statistics at Xi’an Jiaotong University and a research intern at the Gaoling School of Artificial Intelligence, Renmin University of China, advised by Prof. Yong Liu.
My research focuses on mechanistic interpretability, deep learning theory, optimization, and scaling laws. I am especially interested in turning empirical training phenomena into first-principles mechanisms: why models train, where behaviors emerge, and when scaling or optimization rules break.
I also work as an AI Technical Consultant for a Tsinghua-affiliated AI startup developing “AI + K-12 Education” products with the Beijing Dongcheng District Education Commission.
I write research notes on my blog and welcome conversations on these topics. I am currently seeking industry research internships in LLM pre-training and AI theory, as well as PhD positions for Fall 2028. More background: English / 中文.
Research Interests
- Mechanistic interpretability of LLMs
- Training dynamics of finite-width networks
- Optimizer design for LLM pre-training
- Scaling laws and their failure modes
- Deep learning theory and optimization
News
| May 25, 2026 | Our Nora optimizer has been included in the ScalingOpt optimizer library. |
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| Apr 18, 2026 | I joined the ScalingOpt project as a co-maintainer, working on optimizer design for large language model training. |
Latest Posts
| Jun 20, 2026 | DASF：一种闭环的 batch size schedule-free 方法 |
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| Jun 16, 2026 | 为什么 LLM pretrain 过程中途要把 batch size 翻倍 |
| Jun 03, 2026 | 不要只学习 19 世纪的西方：文明中心论、世界主义与青年领袖的公共责任 |
| May 24, 2026 | 重听杨植麟：Bet on Scaling、第一性原理和长期主义 |
| May 15, 2026 | μP Map |
