Full-Stack Developer and AI Enthusiast Candidate

Kim Ngan Tran

*******@***.*** • (***) *** - **** • LinkedIn • Github

EDUCATION University of Illinois at Chicago Expected Graduation: May 2027 Bachelor of Science in Computer Science Chicago, IL

● Relevant Coursework: Data Structures, Program Design, Programming Practicum, Languages and Automata, Discrete Mathematics, Applied Linear Algebra, Natural Language Processing, System Programming SKILLS Programming Languages: Python, C, C++, Java, JavaScript, HTML, CSS, Go, F#, SQL Frameworks & Libraries: React, Node.js, Express, Flask, PyTorch, TensorFlow, BERT, Bootstrap, Pygame, Tkinter Tools & Platforms: Git/GitHub, Docker, CI/CD, Linux, Windows, macOS, VS Code Concepts: Data Structures, Algorithms, Multithreading, Distributed Systems, Event-Driven Design, REST APIs Certification: Introduction to Front-End Development (Meta) PROJECTS TodoList Web App Javascript, HTML, React, Node.js, MongoDB, Tailwind 4, Shadcn January 2026

● Built full-stack task management app with Node.js/Express/MongoDB, handling 50+ CRUD operations.

● Designed responsive React UI with Tailwind CSS and Shadcn, achieving < 200ms interaction latency.

● Implemented real-time sync across 5 concurrent sessions using REST APIs and React state management. ThreeCard Poker Java, JavaFX, Maven, Java Sockets, Multithreading, Git, Figma November 2025

● Built multiplayer 3-Card Poker game with Java Sockets supporting 8 simultaneous players.

● Developed multithreaded event-driven architecture with server and client threads isolated from JavaFX UI.

● Maintained independent game state with separate decks and histories per client-server session. Keno Game Java, JavaFX, Maven, Event-Driven Programming, Figma October 2025

● Developed JavaFX Keno casino game using Java, JavaFX, and Maven with event-driven architecture for number selection and matching.

● Implemented game logic with random number generation for 20-number draws, duplicate prevention, wager validation.

● Built interactive GUI enabling real-time number selection, drawing animations, and win/loss calculations. NLP Emotion & Empathy Prediction Python, PyTorch, Transformers, BERT, LLMs, Git September 2025

● Implemented corpus-based and in-context learning chatbots generating empathic responses from WASSA 2024 dataset.

● Fine-tuned BERT and LLMs for contextual dialogue generation in multi-turn conversations.

● Designed modular NLP pipelines with GPU optimization on Google Colab and Git collaboration.

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