I am a second-year M.S. student in Computer Engineering at New York University, with a strong foundation in data structures and hands-on full-stack development experience. I am currently seeking a full-time Software Engineer position starting in May 2026.

My core stack includes Java, Spring Boot, React, and SQL. I focus on building reliable backend services, clean REST APIs, and user-friendly frontend experiences that solve practical problems.

Across academic and personal projects, I enjoy taking ideas from design to deployment. I have worked on end-to-end systems involving authentication, recommendation, search, cloud deployment, and performance optimization.

I am curious about new technologies, proactive in collaboration, and committed to writing maintainable code. I value clear communication, ownership, and steady execution in team environments.

Education

• New York University, Brooklyn, New York, U.S.A
  • Master of Science in Computer Engineering
  • September 2024 - present
• The Ohio State University, Columbus, Ohio, U.S.A
  • Bachelor of Science in Computer Science
  • August 2020 - May 2024

Technical Skills

• Programming Languages: Java, Python, JavaScript, SQL, C, Go, Kotlin, PHP, HTML & CSS
• Frameworks & Libraries: Spring Boot, Express, React, Angular, Android Jetpack, Go Web frameworks, LangChain, Linux, iOS, AWS EC2, Amazon S3, Elasticsearch, Restful API, Google App Engine
• Database & Tools: PostgreSQL, MySQL, Room, Firebase, SQLite, MongoDB, Git, Docker, Apache Tomcat, Kafka, Room Database, Memory Vector Store

Work Experience

Research Assistant

• Mentor: Dr. Alper Yilmaz, PCV Lab, The Ohio State University
• Location: Ohio, U.S.A
• Duration: May 2023 - December 2023
• Implemented an object detection system using the YOLOv5 model and DeepSORT algorithms to analyze stadium crowds in both pictures and videos, effectively tracking the crowd movements.

Software Developer Internship

• Company: RUI Technology Co., Ltd
• Location: Shenzhen, China
• Duration: May 2023 - August 2023
• Developed a Python-based automated testing framework using Django, which streamlined the collection and analysis of key LCD/LCM parameters (response time, color accuracy, brightness uniformity), reducing the testing cycle by approximately 40%.
• Leveraged Python libraries such as pandas, NumPy, and Matplotlib to preprocess and visualize complex testing data. This enabled the team to quickly identify performance bottlenecks and informed critical product enhancements.
• Created dynamic Python scripts to adjust testing parameters for different display models, ensuring high precision in performance assessments and significantly boosting product quality and market competitiveness.

Software Developer Internship

• Company: RUI Technology Co., Ltd
• Location: Shenzhen, China
• Duration: May 2021 - August 2021
• Utilized Python to interface with specialized equipment (e.g., spectrum analyzers and image quality assessment tools), automating the collection of essential LCD performance data such as response time and color fidelity.
• Implemented Python solutions for real-time data monitoring and logging, which improved the accuracy and repeatability of tests while reducing manual data entry errors.
• Conducted in-depth data analysis with Python to generate comprehensive reports, providing actionable insights that directly influenced product optimization strategies and enhanced overall display performance.

Practical Experience

Twitch+: A Personalized Twitch Resources Recommendation Engine

• Designed and built a full-stack Spring Boot application deployed to AWS App Runner for users to search Twitch resources and get recommendations, along with a user-friendly frontend using React and Ant Design.
• Implemented RESTful APIs to retrieve real Twitch resources via Twitch API with OpenFeign HTTP client, and managed user authentication (register/login/logout) using Spring Security.
• Extracted game information from Twitch resources to implement a content-based recommendation solution based on favorite collections, utilizing MySQL on AWS RDS, Spring Data JDBC, and optimized performance with Caffeine caching.

Staybooking: An Online Stay Rental Application

• Architected a single-page web application using React and AntD for the frontend, supported by backend services built on Spring Boot to manage stay uploads, deletions, searches, and reservations.
• Utilized PostgreSQL to store user-generated data and reservation history, integrated Google Cloud Storage for media files, and deployed the highly scalable backend service to Google Cloud Run.
• Implemented secure token-based server-side user authentication leveraging the Spring Security framework.

OnlineOrder: A Spring Boot Based Online Food Ordering System

• Architected an online food ordering system using Spring Boot, with clear separation of structure into controllers, services, repositories and utilizing dependency injection to enhance maintainability and scalability.
• Constructed the frontend using React and CRUD REST APIs controllers, encompassing functionalities such as registration, menu searching, ordering, and check out. Deployed on AWS for efficient deployment.
• Developed Spring Data JDBC with PostgreSQL database and hosted on AWS RDS, handling data related to menus, shopping carts and restaurant operations.

SocialAI: An AI-Based Social Network

• Implemented a social network platform using React, focusing on user-friendly design and seamless interaction. Utilized OpenAI’s Dall-E 3 to assist users in creating and update posts.
• Used scalable web service in Go to handle posts and ElasticSearch (Deployed to Google App Engine) to provide search functionalities for users to search recent posts.
• Improved the authentication using token-based registration/login/logout flow with React Router v4 and server-side user authentication with JWT.

Next AI: Full-Stack Web-Based Interactive AI Agent for PDF Document Queries

• Architected an interactive conversational UI leveraging React and Ant Design, enabling users to effortlessly upload and interact with PDF documents in real-time.
• Architected and implemented RESTful APIs via Express and Node.js, optimized for high performance request handling.
• Integrated OpenAI’s GPT-3.5 Turbo API and LangChain technologies, achieving a sophisticated AI agent capable of document uploading, splitting, storage, retrieval, and output functionalities.

Mini Spotify: Mobile Music Application

• Designed a Kotlin Spotify app by fully leveraging Android Jetpack Library and Hilt Dependency Injection.
• Implemented the BottomBar & app Navigation using Jetpack Navigation component, and created RESTful APIs with json-server and used Retrofit to handle requests.
• Built the feed/album/favorite UI in Jetpack Compose following MVVM architecture and enabled the local cache ability for the favorite music feature by using Room Database.

Publication

• Jun Liu, “Application of Object Detection in Autonomous Driving,” 2023 International Conference on Artificial Intelligence, Computers and Big Data (AICBD 2023).