Curriculum Vitae

Personal Information

Name: Xutian Chen
Email: chenxutian@buaa.edu.cn
GitHub: github.com/Blossom0913
Gitee: gitee.com/chenxutian

Master of Engineering in Electronic Information
September 2025 – Present | Beijing, China

Major Courses: Machine Learning, Deep Learning, Computer Vision and 15 others

Bachelor of Engineering in Artificial Intelligence
September 2021 – July 2025 | Zhuhai, China

A+ Courses: Computer Network, Data Structure, Advanced Programming Language and 15 others

Algorithm Intern
February 2025 – September 2025 | Zhuhai, China

Applied for 2 software copyright certificates as Top-3 co-author:
- Logistics warehouse multi-intelligent robot path planning system
- Lightweight tool platform based on point task management and billing tracking
Designed experiment framework for mouse social behavior classification, using DeepLabCut to label body coordination and LightGBM compared with LSTM, CNN, GMM model performance
Completed 43.8 million small molecules docking experiment, a large-scale computing task in drug development. Designed parallel framework and deployed on 4 RTX 2080Ti GPUs
Source code available at: Dock Repository

Team Member
November 2021 – June 2022 | Zhuhai, China

National Second Prize in ASC 2022, ranked 22nd among all participants
Attended the ASC final as visitors at USTC in July 2022
Focused on DeepMD-Kit and High Performance Computing (HPC)
Optimized benchmarks by parallelizing computation with CUDA, MPI, OpenMP and other tools
Achieved 11% performance optimization
Assisted in configuring remote servers, running environment preparations and data visualization
Work documented in: ASC Student Supercomputer Challenge Proposal

Research Assistant
March 2024 – July 2024 | Zhuhai, China

Software developer in research group, designed and implemented message interaction models for information communication between AGV platform and local server
Reproduced the baseline of CL-CBS, a multi-agent path planning algorithm designed by APRIL Lab of Zhejiang University
Modified and applied algorithm to simulation AGV platform: CL-MAPF: Multi-Agent Path Finding for Car-Like Robots with Kinematic and Spatiotemporal Constraints
Cooperated with team to investigate and analyze feasibility of CL-CBS in real business scenarios
Fixed bugs and proposed strategies achieving 5x speed improvement over original algorithms like Hybrid A* in 3-month period

Designed and built a time management APP from scratch
Learned Version Control Systems (VCS), Event Response and basic debugging tools in Android Studio
Designed UI/UX with ViewPage2, TabLayout and Fragment independently
Source code: Blossom0913/PlayTask

Python: Advanced proficiency in data science, machine learning, and backend development
C/C++: Strong foundation in system programming and algorithm optimization
Java: Experience in enterprise applications and Android development
Rust: Growing expertise in systems programming and performance-critical applications
Kotlin: Android app development and modern JVM applications

Development Tools: Git, SSH, Android Studio
High Performance Computing: CUDA, MPI, OpenMP, parallel computing frameworks
Machine Learning: TensorFlow, PyTorch, model fine-tuning, deep learning architectures
Operating Systems: Linux administration, Shell scripting, system optimization
Other Technologies: Algorithm design, multi-agent systems, computer vision, Lisp programming

2022: 🥈 National Second Prize in ASC2022 (Student Supercomputer Challenge), ranked 22nd among all participants

Machine Learning & Deep Learning: Advanced neural network architectures, optimization algorithms
Computer Vision: Image processing, object detection, pattern recognition
Multi-Agent Systems: Path planning, coordination algorithms, distributed computing
High Performance Computing: Parallel algorithms, GPU computing, distributed systems
Bioinformatics: Molecular docking, computational drug discovery

Last updated: September 2025