• 🎓 Double Major: Geospatial Information Engineering and Electrical & Electronic Engineering
• ☁️ Education: Hyundai Autoever Cloud Training (3rd Batch)
• 🔭 Focus: Scalable Backend Systems, Cloud Native Infrastructure, and Spatial Data Pipelines
• 💡 Key Interest: Automating CI/CD/CT pipelines and optimizing CDC(Change Data Capture) workflows

• Network & Security: TCP/IP, NAT, Firewall(UFW/IPTables), Kernel & Shell Scripting

• Data Engineering: CDC(Postgres to Mongo), Data Modeling

Experience analyzing spatial and positioning data relevant to navigation and mobility services.

• GNSS signal quality analysis (SNR, DOP)
• RTK-GPS vs Smartphone positioning comparison
• Satellite geometry and multipath analysis
• Spatial accessibility analysis using GIS
• Spatial data processing and coordinate transformation

This experience builds the foundation for navigation data analysis and HD Map data understanding.

• Description: Team mini project for developing an EV charging station information service during Hyundai Autoever Cloud Training program
• Role: - Role: Backend API implementation and containerized service deployment with CI/CD automation using Docker, Kubernetes, and Jenkins
• Key Skills: FastAPI, PostgreSQL(PostGIS), MongoDB, Docker, Docker Compose, Kubernetes, Kafka, Debezium, Jenkins
• Focus: Implementing backend APIs, managing containerized services, configuring Jenkins-based CI/CD pipeline for automated Docker image build workflow, and deploying the system on Kubernetes with a CDC-based data pipeline
• Architecture: Kubernetes-based microservice architecture with Nginx gateway, FastAPI backend services, PostgreSQL(PostGIS) primary database, Jenkins CI/CD pipeline, and CDC data pipeline using Debezium, Kafka, and MongoDB

RTK-GPS와 스마트폰 GNSS 데이터를 비교하여 환경 변화가 위치 정확도에 미치는 영향을 분석하였다.

Key Analysis

• NMEA Raw Data Parsing
• SNR / DOP 분석
• Satellite Geometry 영향 분석
• SP3 Precise Orbit 기반 위성 위치 비교

조석 변화(만조 / 간조)에 따른 GNSS 신호 반사 및 SNR 변화를 분석하였다.

영상 정합 및 좌표 변환 모델을 구현하여 모델별 정확도를 정량적으로 비교하였다.

Key Implementation

• Affine Transformation
• Homography Transformation
• DLT Coordinate Transformation
• Precision Sensor Model (EOP correction)

Homography 모델이 특정 평면에서 Affine보다 낮은 RMSE를 보였다.

Analysis Workflow

Risk Layer (Cardiac Arrest Rate)
↓
Demand Layer (Land Cover + Population)
↓
Accessibility Analysis (Service Area)
↓
Weighted Overlay
↓
Location Allocation

Key Result

• 기존 응급실 커버리지: 1060.03 km²
• 추가 후보지 적용 후: 1176.35 km²
• 증가 면적: +116.33 km²

Inha University
B.S. in Geospatial Information Engineering
Double Major: Electrical and Electronic Engineering

Relevant Coursework

• GIS Introduction
• Photogrammetry
• GPS and Satellite Positioning
• Spatial Analysis
• Object-Oriented Programming
• Spatial Information Programming

• ADsP (Advanced Data Analytics Semi-Professional) — 2025.03.21
• SQLD (SQL Developer) — 2024.09.20

Responsibilities

• 학과 행사 기획 및 운영
• 사업 계획서 및 예산 관리
• 공지 및 홍보 관리
• 멘토링 프로그램 운영
• 간식드리미 행사

대표 행사

• 선배와의 만남
• 학과 연합 체육대회
• 학과 멘토링 프로그램

Python 기초 프로그래밍 교육 진행

Teaching Topics

• 조건문
• 반복문
• 자료형
• 배열, 2차원 배열
• 리스트
• 파일 핸들링
• 기본 알고리즘 문제 풀이