I’m a hands-on builder who is willing to take on anything that offers a chance to learn through experience.
I am curious about a wide range of technologies and enjoy continuously learning, experimenting, and expanding my interests across different fields.
A full-stack movie discovery and recommendation platform that combines personalized browsing with RAG-powered conversations in the voices of movie characters.
Highlights
- Personalized movie search, recommendations, rankings, and activity tracking
- One-on-one and group conversations with supported movie characters
- RAG pipeline with intent routing, embedding retrieval, and reranking
- React, FastAPI, PostgreSQL, Milvus, Docker, and Kubernetes integration
An experimental pipeline for converting handheld indoor RGB video into rough 2D floor-plan drafts.
The project combines camera pose estimation, semantic segmentation, and monocular depth estimation to accumulate spatial evidence in a shared top-down coordinate system.
Highlights
- RGB-only indoor spatial reconstruction
- Semantic segmentation and monocular depth estimation
- COLMAP-based camera pose analysis
- Top-down free-space and wall-boundary reconstruction
- Experiment documentation, failure analysis, and feasibility validation
A reproducible data analysis and machine learning experiment for predicting whether an AI job belongs to the high-salary class.
The project compares five classification models, tracks experiments with MLflow, and manages the dataset with DVC.
Highlights
- AI job market salary data preprocessing and analysis
- Logistic Regression, Random Forest, XGBoost, LightGBM, and CatBoost
- Stratified train-test split and class-imbalance handling
- Accuracy, precision, recall, F1, ROC AUC, PR AUC, and log-loss evaluation
- MLflow experiment tracking and Model Registry integration
- DVC-based dataset version management
- Indoor spatial reconstruction from mobile video using depth estimation and camera pose analysis
- Data analysis and insight discovery through real-world datasets
- Reliable RAG pipelines and retrieval quality
- Infrastructure architecture, container orchestration, cloud deployment, and scalable system operations
