- 🎨 I'm a passionate Machine Learning Engineer with a strong background in data statistics.
- 🤖 Deeply interested in LLM applications, currently studying about hallucination
- 🛠 Created various open-source libraries:
- 🔍 ThreatLens - An anomaly detection system built on the NSL-KDD dataset. Classifies network traffic into normal vs. abnormal (e.g., DDoS, scans), with model explainability (ELI5, Alibi) and Django-based web interface for real-time threat monitoring. 📑 Paper & 📊 Poster
- 💊 Autofic - A system that automatically detects security vulnerabilities in code, applies patches, and generates PR for seamless integration 📑 Paper & 📊 Poster & 🥇 Award
- 🏠 PRIME - This is a dynamic web dashboard that visualizes 290,000 real estate transaction records on a map using Dash/Plotly, with the data stored in Supabase. [Developing]
- 🧑🏻💻 Blog - This is the technical learning log of an aspiring developer committed to reading 100 books and 200 papers before graduation, sharing the journey to help others in the field.
- 🎓 Undergraduate student majoring in Computer Science, specializing in Artificial Intelligence
- University of Utah — Salt Lake City, UT, USA Exchange Student, Computer Engineering (Aug 2025 – Dec 2025)
- 👾 Programming is something I truly enjoy, and I'm always excited to create something new
- 📖 Interested in Large Language Model optimization, with a focus on efficient fine-tuning (LoRA, PEFT) and hallucination reduction through retrieval-augmented generation.
- 🌍 Passionate about multilingual NLP, especially in low-resource settings and cross-lingual transfer.
- 🔍 Exploring explainability in NLP models, leveraging XAI techniques to make model decisions more transparent and trustworthy.