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Jiayue Yang

杨家越 | Computer Science @ USTC
在海中也要望月，在谷底也要生花。

I'm Jiayue Yang, a second-year Computer Science major at USTC. Exploring the intersection of programming and AI fundamentals.

Supervisor: Prof. Dr. Yan Xia at SPIN-Lab, School of Artificial Intelligence and Data Science, University of Science and Technology of China.

UK visit (June–September): University of Cambridge, under guidance of Prof. Dr. Olaf Wysocki and Prof. Dr. Brian Sheil. Associated units: CV4DT and Smart Infrastructure Lab.

🏫
School of Computer Science and Technology
University of Science and Technology of China
📌 Hefei, Anhui, China

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🚀 Research Interests Currently Focusing on 3D Vision

  • Computer Vision
  • Spatial Intelligence
  • Multimodal Large Language Models
  • Embodied AI

💻 Current Focus

🔧 Core Skills
Python 85%
C 70%
📚 Coursework

CS61A (Structure & Interpretation)
CS221 (AI Fundamentals)

🛠️ Tools

Git • Linux • PyTorch • OpenCV

🎯 Interests & Hobbies

  • 🏀 Basketball
  • 🏓 Table Tennis
  • 🌏 Traveling
  • 📷 Photography
  • 🍜 Foodie

📧 Contact

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📧
💼

📢 Announcements

🎉 Our work has been accepted to the CVPR 2026 Main Conference.

🎓 Education

2024 - 2028 (Expected)
B.S. in Computer Science and Technology
University of Science and Technology of China (USTC)

Huaxia Computer Science and Technology Elite Class, Department of Computer Science and Technology.

💼 Work Experience

May 2025 - Present
Research Assistant
SPIN-Lab, USTC

Conducting research in computer vision, spatial intelligence, multimodal large language models, and embodied AI.

June – September 2025
Research Visit
University of Cambridge, under guidance of Prof. Dr. Olaf Wysocki and Prof. Dr. Brian Sheil

Associated units: CV4DT, Smart Infrastructure Lab. Conducting research in 3D computer vision, focusing on 3D reconstruction for semantic reconstruction and digital twins applications.

July 2025 - Present
Student Assistant
Foreign Language Teaching Center, USTC

Supporting foreign language education initiatives and administrative tasks.

📚 Publications

Xuewei Cao, Jiayue Yang, Zhiwen Zeng, Yanyong Zhang, Yan Xia†.
C-LaV: Conditional Latent Velocity Field Denoising for Weather-Robust LiDAR Place Recognition.
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

📚 Publications

Research in Progress

As an undergraduate researcher, I'm currently working on several projects in computer vision and spatial intelligence. Publications will be added as research progresses and papers are accepted for conferences and journals.


Stay tuned for updates on my research contributions!

🎤 Talks

Speaking Opportunities

I look forward to sharing my research findings and insights with the academic community through conferences, seminars, and workshops. This section will be updated with information about upcoming and past presentations.


Check back for future speaking engagements!

👨‍🏫 Teaching

Teaching Opportunities

As I progress in my academic journey, I'm interested in sharing knowledge through teaching assistant positions, tutoring, and mentoring opportunities. This section will showcase any teaching experiences and educational contributions.


Future teaching roles and experiences will be documented here!

💼 Portfolio

🚀 Featured Projects

2025 - Present
Computer Vision Research
SPIN-Lab, USTC

Working on spatial intelligence, multimodal large language models, and embodied AI projects under the supervision of Prof. Dr. Yan Xia. Focusing on developing algorithms for visual understanding and spatial reasoning.

2025
CS221 AI Project
Artificial Intelligence Fundamentals

Implemented and analyzed various AI algorithms including search algorithms, machine learning models, and logical reasoning systems.

2024
CS61A Programming Projects
Structure and Interpretation of Computer Programs

Completed comprehensive programming assignments including implementing interpreters, data structures, and functional programming concepts in Python.

November 2025 - Present
Research Intern
Computer Vision for Digital Twins (CV4DT), Centre for Smart Infrastructure and Construction (CSIC), University of Cambridge

Supervised by Prof. Dr. Olaf Wysocki. Conducting research in 3D computer vision, focusing on 3D reconstruction techniques for semantic reconstruction and digital twins applications.

🛠️ Technical Skills

Python
C/C++
Git
Linux
PyTorch

📄 Curriculum Vitae

🎓 Education

2024 - 2028 (Expected)
B.S. in Computer Science and Technology
University of Science and Technology of China (USTC)

Huaxia Computer Science and Technology Elite Class, Department of Computer Science and Technology. Specialized program focusing on advanced computer science curriculum and research opportunities.

💼 Work Experience

May 2025 - Present
Research Assistant
SPIN-Lab, USTC · Supervisor: Prof. Dr. Yan Xia

Conducting research in computer vision, spatial intelligence, multimodal large language models, and embodied AI. Working on projects related to visual understanding, spatial reasoning, and AI applications in computer vision tasks.

July 2025 - Present
Student Assistant
Foreign Language Teaching Center, USTC

Supporting foreign language education initiatives and assisting with administrative tasks in the language teaching center.

November 2025 - Present
Research Intern
Computer Vision for Digital Twins (CV4DT), Centre for Smart Infrastructure and Construction (CSIC), University of Cambridge · Supervisor: Prof. Dr. Olaf Wysocki

Conducting research in 3D computer vision, focusing on 3D reconstruction techniques for semantic reconstruction and digital twins applications.

📚 Relevant Coursework

CS61A - Structure and Interpretation of Computer Programs
CS221 - Artificial Intelligence Fundamentals
Data Structures and Algorithms
Linear Algebra

💻 Technical Skills

Programming Languages

Proficient: Python, C/C++
Familiar: JavaScript, MATLAB

Frameworks & Tools

PyTorch, NumPy, Git, Linux, Jupyter Notebooks

🏆 Achievements

Completed CS61A with distinction
Research assistant at SPIN-Lab, USTC

📧 Contact Information

Academic Email: jiayueyang@mail.ustc.edu.cn
Personal Email: jiangjiayue06@gmail.com
GitHub: github.com/jryyangjy
Hugging Face: huggingface.co/jryyangjy
LinkedIn: linkedin.com/in/jiayue-yang-562008377
Twitter: twitter.com/jryyangjy
Bluesky: jryyangjy.bsky.social
Location: Hefei, Anhui, China

🌐 Languages

Chinese (Mandarin): Native
English: Fluent (Academic and Technical)

🎯 Interests & Hobbies

🏀 Basketball
🏓 Table Tennis
🌏 Traveling
📷 Photography
🍜 Foodie

📖 Academic Guide

🎯 Study Tips for Computer Science

Programming Fundamentals
Start with understanding basic concepts rather than memorizing syntax. Practice coding regularly and focus on problem-solving approaches. Use resources like CS61A to build strong foundational knowledge.
Research Involvement
Engage with professors early in your academic journey. Don't be afraid to reach out to research labs and express genuine interest in their work. Consistent effort and curiosity are more valuable than prior experience.
Building Technical Skills
Focus on understanding core concepts in algorithms, data structures, and mathematics. Supplement coursework with personal projects and open-source contributions. Learn version control (Git) early.

📚 Recommended Resources

  • CS61A Berkeley: Excellent introduction to programming and computer science concepts
  • CS221 Stanford: Comprehensive AI fundamentals course
  • PyTorch Documentation: Essential for machine learning and deep learning projects
  • OpenCV Tutorials: Great starting point for computer vision applications
  • GitHub: Build a portfolio of projects and collaborate with others

🚀 Getting Started in Research

Finding Your Interest
Explore different areas through coursework and reading recent papers. Attend seminars and research presentations to understand current trends and challenges in computer science.
Building Connections
Network with graduate students, attend lab meetings when possible, and participate in academic conferences. Join study groups and collaborative projects with peers.

🚀 Projects

Selected personal repositories and experiments
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Q-learning with visualization
A Q-learning implementation with interactive visualizations to demonstrate RL concepts and learning dynamics.
Python Reinforcement Learning
📖 View on GitHub
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VAE
Variational Autoencoder experiments including training scripts and sample reconstructions.
PyTorch Generative Models
📖 View on GitHub