XINYU

Hello, I'm Xinyu.

I work on Computer Vision

About Me

Xinyu Tian portrait

Xinyu Tian

MSc, National University of Singapore

Computer Vision · Machine Learning · AI Applications

I'm Xinyu Tian, a Master's student at the National University of Singapore (NUS). I'm interested in any technology that can be translated into real products and meaningfully improve people's lives. Recently, my work has focused on computer vision and AI applications.

I also document my journey as a bilingual content creator, sharing stories about learning, travel, and personal growth. Switch to Life mode to learn more.

🎓 NUS MSc Physics🔬 A*STAR Research🗣️ Mandarin · English
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Computer Vision

Visual perception for the physical world — detection, and scene understanding, from industrial imaging to 3D perception.

🤖

AI Applications

Applying CV/ML models to practical products — focused on reliability and deployment.

Open to full-time CV/ML Engineer roles · Starting from Feb 2027

News

  • 04/2026NEWCompleted Research Internship at A*STAR
  • 08/2025Joined A*STAR as Research Intern
  • 08/2025Started MSc Physics for Technology at NUS
  • 06/2025Graduated from SWJTU with BSc in Applied Physics
  • 09/2021Started Applied Physics BSc at SWJTU

Experience

Internships and Professional Experience

  • Built an end-to-end CNN-based defect detection pipeline for AOG identification on wafer SEM images.
  • Curated and pixel-annotated 288 high-resolution SEM images using CVAT to construct the training set.
  • Benchmarked classical intensity baseline, plain UNet, and ResNet34-UNet — improved IoU, Dice, and F1 under identical settings.
  • Deployed the model as an application prototype reporting defect count, location, area, and batch-level statistical charts.
Python
PyTorch
OpenCV
Docker
CVAT
ResNet
UNet

Skills

Technical Skills and Languages

Programming

Python
C
C++
JavaScript
TypeScript
Next.js

Computer Vision & Machine Learning

PyTorch
TensorFlow
OpenCV
NumPy
scikit-learn

Tools

GitHub
Git
Docker
Linux
Jupyter
Anaconda
LaTeX
Vercel

AI-Assisted Development

Claude CodeClaude Code
CodexCodex
ChatGPTChatGPT
CursorCursor
GitHub CopilotGitHub Copilot

Projects

Selected Work and Research Experiences

SEM Image Defect Detection

Case Study

Semantic segmentation and defect detection for industrial SEM imagery, focusing on robustness and deployment-ready design.

Computer VisionPyTorchU-Net
View Details ->

RGBD Multimodal Object Recognition

Case Study

A data pipeline and dashboard for logistics tracking, KPI visualization, and operational insights.

Data AnalyticsPythonVisualization
View Details ->

NUS Life & Travel Vlogs

Case Study

Short-form video content documenting campus life, Singapore culture, and travel stories.

Content CreationVideoStorytelling
View Details ->

Education

Academic Background and Qualifications

  • Researching deep learning-based semantic segmentation and anomaly detection for industrial SEM imaging.
  • Developing end-to-end CV pipelines with PyTorch for deployment-ready prototypes.
  • Collaborating with research groups on AI-driven solutions for advanced manufacturing quality control.
Computer Vision
Machine Learning
Python
PyTorch
OpenCV
English Communication
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  • Completed coursework in optics, electromagnetism, quantum mechanics, and computational physics.
  • Conducted experimental research in laboratory settings, developing strong data analysis and instrumentation skills.
  • Graduated with honours, building a foundation for graduate-level research in applied sciences.
C
C++
Python
MATLAB
NumPy
Public Speaking
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Contact

Let's Connect

I'm open to roles in computer vision and AI applications, collaborations, and internship opportunities. Reach out if you want to work together or discuss ideas.