Bi Bi Rafiya Begum

Java & Full-Stack Developer · AI-Integrated Systems

Chikkamagaluru, Karnataka, India

@rafiya

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🎓 Bachelor of Engineering in Computer Science & Engineering at Visvesvaraya Technological University (VTU) · Graduating 2027

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About

Computer Science undergraduate specializing in Java, full-stack web development, and database systems, with hands-on experience building AI-integrated applications. Seeking an entry-level Java or Software Developer role to apply a strong technical foundation to real-world engineering problems.

Education

2027

Bachelor of Engineering

Adichunchanagiri Institute of Technology

Awarded by Visvesvaraya Technological University (VTU)

Computer Science · 2027

Computer Science

Skills

<3 months

C CSS RAG Oop HTML Java JDBC Array Python Django OpenCV Queues FastAPI PyTorch JavaScript Linked List Advanced DBMS Computer Networks Data Structures and Algorithms

Tools / apps / platforms

<3 months

MySQL Ollama

Languages

Fluent

Urdu Speak Hindi Speak English Speak Kannada Speak

Projects

Library Management System

Java, JDBC, MySQL, Swing (GUI)

Built a desktop application in Java with a Swing-based GUI to manage book inventory, member records, and issue/return transactions. Used JDBC to connect the application to a MySQL database, implementing CRUD operations for books and members with due-date tracking. Applied core OOP principles to structure the application into reusable modules for authentication, catalog management, and transaction handling.
AI-Based Learning Platform for JEE & NEET Students

HTML, CSS, JavaScript, AI Tools

Developed an AI-assisted educational platform to support exam preparation for JEE and NEET aspirants. Integrated AI-driven tools into the platform and designed an accessible, easy-to-use learning interface.
E-Commerce Website for Vintage Cars

Django, HTML, CSS, JavaScript, MySQL

Developed a responsive e-commerce web application for vintage car listings using Django and MySQL. Implemented user authentication, car listing management, and search functionality with a user-friendly interface.
AI-Based Pressure Ulcer Image Analysis

Python, ResNet50, U-Net, PyTorch, OpenCV, Grad-CAM, FastAPI, RAG, Ollama

Built an AI-powered medical image analysis system for automated pressure ulcer segmentation, staging, and area estimation using U-Net and ResNet50 architectures. Designed a Gemma + RAG chatbot to deliver personalized, explainable predictions and wound-care guidance, combining retrieval-augmented generation with Grad-CAM visual explanations for clinical interpretability. Built end-to-end using FastAPI, integrating model inference with a conversational interface for healthcare support use cases.

Courses & certifications

Networking Protocols · NPTEL · 2024
Database Management Systems · NPTEL · 2023
Design and Analysis of Algorithms · NPTEL · 2023

🎯 Hobbies & interests

Solving puzzles and logical problems
Learning new technologies
Watching Podcasts
Driving

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