CV
Academic CV for Jiaxuan Zou.
Contact Information
| Name | Jiaxuan Zou |
| Professional Title | Undergraduate Student in Mathematics and Statistics |
| 3140143497@qq.com | |
| Location | Xi'an, Shaanxi |
| Website | https://jiaxuanzou0714.github.io |
Professional Summary
Undergraduate in Mathematics and Statistics at Xi’an Jiaotong University and research intern at the Gaoling School of Artificial Intelligence, Renmin University of China. My work focuses on mechanistic interpretability, training dynamics, optimizer design, and scaling laws.
Experience
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Beijing, China
Research Intern
Gaoling School of Artificial Intelligence, Renmin University of China
Advised by Prof. Yong Liu.
- Work on mechanistic interpretability, deep learning theory, optimizer design, and scaling laws.
- Co-authored preprints on linear attention, neural scaling laws, latent chain-of-thought, and matrix optimizer design.
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2026 - Present Remote
Co-maintainer
ScalingOpt
A project on optimizer design for large language model training.
- Work on the relation among optimizer design, model architecture, and training configuration under scaling-law regimes.
- Help maintain the optimizer library, including the Nora optimizer entry.
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Beijing, China
AI Technical Consultant
Tsinghua-affiliated AI startup
- Consult on “AI + K-12 Education” products developed with the Beijing Dongcheng District Education Commission.
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2024 - Present Xi'an, China
Founder and Organizer
Xi'an Jiaotong University Deep Learning Seminar
- Started an undergraduate deep learning seminar at Xi’an Jiaotong University.
- The seminar later attracted more than one thousand participants from across China and led to research collaborations.
Education
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2024 - Present Xi'an, China
Undergraduate Student
Xi'an Jiaotong University
Mathematics and Statistics
- School of Mathematics and Statistics.
- Research interests include deep learning theory, optimization, mechanistic interpretability, and scaling laws.
Projects
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ScalingOpt
A discussion platform and benchmark project for optimizer design in large language model training.
- Co-maintainer.
- Focuses on optimizer design, model architecture, and training configuration under the scaling-law paradigm.
- Nora has been included in the ScalingOpt optimizer library.
Publications
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2026 -
2026 Nora: Normalized Orthogonal Row Alignment for Scalable Matrix Optimizer
Under Review
Jinghui Yuan, Jiaxuan Zou, Shuo Wang, Yong Liu, and Feiping Nie. arXiv:2605.03769.
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2026 Effective Frontiers: A Unification of Neural Scaling Laws
Under Review
Jiaxuan Zou, Zixuan Gong, Ye Su, Huayi Tang, and Yong Liu. arXiv:2602.02593.
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2026 Capabilities and Fundamental Limits of Latent Chain-of-Thought
Under Review
Jiaxuan Zou, Yaozhong Xiong, and Yong Liu. arXiv:2602.01148.
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2026 Statistical MIA: Rethinking Membership Inference Attack for Reliable Unlearning Auditing
Under Review
Jialong Sun, Zeming Wei, Jiaxuan Zou, Jiacheng Gong, Guanheng Wang, Chengyang Dong, Jialong Li, and Bo Liu. arXiv:2602.01150.
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2025 FreIE: Low-Frequency Spectral Bias in Neural Networks for Time-Series Tasks
IEEE ICDM
Jialong Sun, Xinpeng Ling, Jiaxuan Zou, Jiawen Kang, and Kejia Zhang.
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2026 Mamba-Driven and Feature-Fused U-Net for Automatic Seismic Horizon Interpretation
IEEE Transactions on Geoscience and Remote Sensing
Tian Zhang, Jiaju He, Naihao Liu, Jiaxuan Zou, and Yongxiang Jiang.
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2024 Seismic Horizon Picking Using Channel-Independent Multi-Scale UNet
Under Review
Jiaxuan Zou, Naihao Liu, Tian Zhang, Jiaju He, Tao Li, and Jinghuai Gao.
Research Interests
- Mechanistic interpretability of LLMs.
- Training dynamics of finite-width neural networks.
- Optimizer design for LLM pre-training.
- Scaling laws and their failure modes.
- Deep learning theory and optimization.