I am an undergraduate student majoring in Big Data Management and Application at South China University of Technology, Guangzhou, China.

My research interests focus on graph neural networks, structural and spectral graph learning, and scalable graph representation learning.

More recently, I have been working on AIDB and data analytics with LLMs, aiming to develop more robust data agents and enhance the capabilities of LLMs in understanding and processing complex data structures.

🔥 News

• 2026.01: 📄 Submitted one paper for ICML 2026 - currently under review.
• 2026.01: 🚀 Launched the SCUT-BDA Wiki, a collaborative knowledge base for the Big Data Association at South China University of Technology (SCUT BDA).
• 2025.12: 📄 Submitted one paper for TKDD - currently under review.
• 2025.10: 🏅 Achieved a Bronze Medal in the 2025 ICPC Asia Regional Contest.
• 2025.10: 🎉 Awarded the National Scholarship (Undergraduate) for the 2024–2025 academic year.

📝 Publications

🏅 Honors and Awards

• 2025.10 Bronze Medal, The 2025 ICPC Asia Chengdu Regional Contest.
• 2025.10 National Scholarship (Undergraduate), China, Academic Year 2024–2025.
• 2024.10 National Scholarship (Undergraduate), China, Academic Year 2023–2024.
• 2024.11 First Prize, The Chinese Mathematics Competitions for College Students.
• 2022.10 First Prize, Preliminary Round, The 36th Chinese Chemistry Olympiad (CChO).

📖 Education

• 2023.09 - Present, Undergraduate, South China University of Technology, Guangzhou, China.
• 2020.09 - 2023.07, High School Diploma, Xuzhou No.1 High School, Xuzhou, China.

💻 Internships

• 2026.02 - Present, Research Intern, Database Research Group, Tsinghua University, Beijing, China. Working under the supervision of Professor Guoliang Li, focusing on AI-driven database systems, with particular emphasis on the integration of LLMs in optimizing database management processes and query execution.

• 2025.01 - 2026.02, Research Intern, Graph Learning Group, South China University of Technology, Guangzhou, China. Working under the supervision of Assistant Professor Mingqi Yang, contributing to projects in the domain of graph neural networks and scalable graph learning methodologies, with an emphasis on spectral graph learning and hierarchical graph models for large-scale graph data.