About Me
I am an undergraduate student at the School of Mathematics and Statistics, Xi'an Jiaotong University. My research interests focus on several areas of artificial intelligence and its applications.
I am particularly interested in deep learning theory, large language model mechanisms, AI for science, and time series modeling using deep learning approaches.
Education
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Bachelor's Degree
Xi'an Jiaotong University
2024-Present
School of Mathematics and Statistics
Research Interests
Deep Learning Theory
My research in this area focuses on the training dynamics of neural networks and representation theory. I'm interested in understanding the theoretical underpinnings of deep learning models and how they learn and represent information.
Large Language Model Mechanisms
I study the inner workings of large language models, including attention mechanisms, emergent abilities, scaling laws, and interpretability. My research aims to better understand how these models process and generate language.
AI for Science
My work in this area includes applications such as seismic horizon picking using deep learning and protein structure prediction. I'm interested in how AI can accelerate scientific discovery and solve complex problems in various domains.
Time Series Modeling
I research deep learning methods for time series data modeling, exploring how neural networks can effectively capture temporal patterns and dependencies in sequential data.
Publications
Currently no publications available. Check back for updates on my research work.
Research Projects
Neural Network Design for Time Series Modeling
2024-Present
Designing a specialized neural network for time series modeling by leveraging the frequency principles of neural networks.
Deep Learning for Seismic Horizon Picking
2024-Present
Researching deep learning methods for Seismic Horizon Picking. Results will be published in IEEE Transactions on Geoscience and Remote Sensing.
Protein Structure Prediction Using Deep Learning
2024-Present
Developing deep learning approaches for protein structure prediction to advance our understanding of protein folding and function.
Deep Learning Seminar
Introduction to Deep Learning
2025 Spring Semester
This seminar covers fundamental concepts and advanced topics in deep learning. Topics include neural network architectures, optimization techniques, and applications in computer vision and natural language processing. All recordings are available online for students to follow along and learn at their own pace.
Contact Information
jiaxuanzou@stu.xjtu.edu.cn
3140143497@qq.com
School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China