🎀 Hi there my No. visitor!

✨I’m Kaijie Chen, a self-motivated and enthusiastic computer science student with a passion for innovation. I thrive on collaborating with researchers from around the world to generate cutting-edge ideas and create outstanding work together!

🚀Currently, my research interests focus on multimodal, multi-agent, data mining, and graph learning. I enjoy examining and interpreting the world through a mathematical lens, seeking patterns and insights that drive meaningful solutions.

🌈 I’m excited about exploring research opportunities in the United States during the spring and summer of 2025. My goal is to lead a research project with the dedication and drive of a PhD student, contributing to impactful advancements.

🎈 If you’re interested in discussing ideas or collaborating on exciting projects, feel free to connect. Let’s make something amazing together!

🔥 News

• 2024.09: 🎉 I joined research at FinTech Lab for Financial Time Series Prediction
• 2024.02: 🎉 I joined at ADMIS Lab reaserch Spatiotemporal Imputation

📖 Education

• 2022.09 - 2026.06, Tongji University – School of Computer Science and Technology 🎓
  • Bachelor of Computer Science (Elite Class)

🔬 Research Interests

• Efficient Multi-agent System
• Data Mining

🏆 Honors and Awards

• 2024,🥇 First Prize (3/782) in the National College Statistical Modeling Competition, Shanghai ⭐
• 2024,🥉 Bronze Award in the China International Innovation and Entrepreneurship Competition, Shanghai 💫
• 2023 / 2024, 🏆 Social Activity Scholarship, Tongji University (Top 5%) 🌟
• 2023 / 2024, 🏆 Academic Scholarship, Tongji University (Top 15%) ✨
• 2022, 🏆 Outstanding Academic Scholarship (¥10,000) 👑
• 2024,🏆 Outstanding Volunteer for Cloud Teaching (National) 💌

📝 Research Experience

• FinTech Lab 🚀
  Research Assistant, Tongji University, Sep 2024- Present
  • Multi-Agent: Designing efficient methodologies to automate agent workflow generation.
  • Time Series Prediction in Finance: Heterogeneous temporal dynamic graph convolution network for stock trend prediction.
• ADMIS Lab 📚
  Research Assistant, Tongji University, Feb 2024- Sep 2024
  • Point Missing Imputation: Investigated imputation methods for datasets with point-level missingness.
  • Block Missing Imputation：Developed spatiotemporal imputation models for highly sparse chlorophyll-a data.

🏫 Student Activities

• 🔧 Tongji Engineering Class 6
  Academic Representative, Sep 2022 – Sep 2024

• 🎓 Tongji University Academic Guidance and Development Center
  Academic Committee Member, Feb 2024 – Jul 2024