This portfolio guide provides a clear reading path rather than simply listing all projects.
My background spans financial analysis, quantitative modeling, and systems-oriented software development. The projects here emphasize “how problems are decomposed and reframed” rather than just features or model performance.
This portfolio is continuously updated. Each selected project not only describes what was done, but also notes:
- When it was first completed and the context behind it
- When and why it was later refactored
- What problem the current version aims to solve
Reading this portfolio is more like viewing an engineering trajectory that evolves over time.
🔎 Quick Navigation (by Background)
Find the most relevant projects for your field from the table below.
| If you’re looking for… | Suggested Projects | Capabilities & Content |
|---|---|---|
| Finance × AI / Quant / FinTech | GLoVE robo_advisor Meme_stock_analysis_and_prediction | GARCH × deep learning hybrid modeling, modular financial analysis, alt-data |
| LLM / RAG / NLP Systems | Deep Learning HW3 – RAG system IRTM_project Toxic Comment Detector (BERT & GPT) | Retriever/reranker fine-tuning, Traditional Chinese RAG experiments |
| LLM Fine-tuning / Transformer Training | Instruction tuning (QLoRA) Chinese Extractive QA (BERT) | PEFT, span prediction training, prompt & inference strategy design |
| Machine Learning / Deep Learning Foundations | data_analysis AI Cup 3D Medical Imaging | End-to-end modeling, time series forecasting, paper reproduction |
| Systems / Full-stack Engineering | CloudNative_Stadium_System Airlines_DBMS | React + Express, API & load testing, database schema & transaction design |
| Recommendation / Data Mining | BDA2023_final_apriori | Association rule recommendations, translating business problems into models |
| Product-oriented AI Applications | youtube_nlp_analysis | Deriving content strategy and business insights from user data |
| Programming Foundations / Systems Thinking | PBC2021-final windowskill | OOP design, interactive systems, C++ vs Python implementation differences |
🧭 Suggested Reading Paths
- GenAI / LLM → RAG system → IRTM → QLoRA
- Quant / FinTech → GLoVE → Robo-advisor
- Software Engineering / Full-stack → Cloud Native → DBMS
- ML Engineer → Data Analytics → AI Cup
👉 View the Complete Project Timeline
💡 Current Focus Areas
- LLM / RAG system design & optimization
- Verifiable modeling for Finance × AI
- Deployable Machine Learning systems
Suggested Starting Projects
If this is your first visit, I recommend starting with these projects — they represent my thinking at different stages:
1. Airlines_DBMS (Database Design & System Refactoring)
A showcase of how I transformed an academic assignment into a fully operable system.
- Dec 2023 (Original): Learning ER modeling and normalization.
- Feb 2026 (Refactored): Enhanced schema and application layer for real user queries.
2. stock_analysis (Financial Quantitative Workflow)
From simple analysis toward a systematic research workflow.
- Jun 2023 (Original): Basic strategy ideation.
- Mar 2026 (Refactored): Modular data processing with a reproducible experiment structure.
Finally
This portfolio is also my engineering notebook. If you’re here for an interview or collaboration, thank you for starting with this guide.