Computer Engineering student · Product-minded Software Developer
Building reliable financial systems, cross-platform apps, and applied AI products.
- 🎓 Studying Computer Engineering at Handong Global University
- 💼 Frontend/UX Lead for FeeGaChu, contributing shared UI systems and API-integrated financial workflows
- 🏦 Currently focused on financial-domain systems, data integrity, batch processing, and product UX
- 📱 Experienced with Flutter/Firebase applications and React/TypeScript web interfaces
- 🤖 Exploring applied AI through literacy learning, LLM evaluation, and privacy-preserving computer vision
| Period | Focus | Highlights |
|---|---|---|
| 2026 | Financial systems & product engineering | Insurance commission reconciliation, Spring Batch, API-integrated product UI |
| 2025 | Mobile products & applied LLMs | GLANG capstone, eco-driving navigation, and LLM evaluation |
| 2024 | Computer vision & Flutter | Automatic face anonymization experiments and cross-platform application development |
| 2021–2023 | Software foundations | C/C++ open-source practice followed by Java, JSP, MyBatis, and web application projects |
Frontend/UX Lead · React · TypeScript · Java · Spring Boot · PostgreSQL
An insurance commission reconciliation platform for split payments, clawbacks, reconciliation, and 1200% rule validation. I work across Figma-driven UI integration, shared workflow components, contract and commission screens, and the APIs that support those user flows.
Capstone contributor · Flutter · Firebase · LLM APIs
An AI-assisted literacy learning application. My contributions include learning-progress and course-data persistence, authentication improvements, database integration across reading activities, localization, and GPT prompt refinement.
Main developer · Flutter · Riverpod · Firebase · Tmap UI SDK
An eco-driving navigation demo with social login, trip-event analysis, eco scores, missions, rankings, and a point shop. I contributed as one of the main developers across navigation, state management, and application flows.
Python · OpenCV · RetinaFace · FaceNet
A computer-vision project exploring automatic face anonymization in video, including reference-face matching, distance filtering, embedding caching, and multiple blur strategies.
- LLM Model Comparison — evaluation framework for literacy-learning prompts across multiple LLMs using BLEU and ROUGE
- Pokemon Unite — a maintained Flutter/Firebase web app for organizing custom matches
| Area | Technologies |
|---|---|
| Backend | Java, Spring Boot, Spring Data JPA, Spring Batch, MyBatis |
| Frontend & Mobile | React, TypeScript, JavaScript, Flutter, Dart |
| Data & Delivery | PostgreSQL, Oracle, H2, Supabase, Firebase, Docker, Vercel |
| AI & Computer Vision | Python, OpenCV, RetinaFace, FaceNet, LLM APIs |