Ananya Ray

Aspiring Software Developer | Full-Stack & Machine Learning Enthusiast

Bhubaneswar, IN.

About

Highly motivated Bachelor of Technology student with a strong foundation in full-stack web development and machine learning, seeking to leverage technical expertise in challenging software development roles. Proven ability to build scalable applications using MERN stack, FastAPI, and Docker, coupled with experience in developing predictive ML models with high accuracy. Eager to contribute to innovative projects and drive impactful solutions.

Work

East Coast Railway

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Web Development Intern

Bhubaneswar, Odisha, India

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Summary

Led the development of a MERN stack-based Appointment & Leave Management System, enhancing operational efficiency for East Coast Railway employees.

Highlights

Developed a comprehensive MERN stack (MongoDB, Express.js, React.js, Node.js) Appointment & Leave Management System, incorporating secure JWT-based authentication and a responsive React UI for East Coast Railway employees.

Built robust RESTful APIs to enable admin-only controls, facilitate date-based leave tracking, and implement efficient appointment filtering, significantly streamlining internal processes.

Collaborated effectively with a team to deliver a functional prototype, ensuring the solution aligned with real-world use cases and met organizational requirements.

Education

Odisha University of Technology and Research

Bhubaneswar, Odisha, India
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Bachelor of Technology Information Technology Grade: CGPA: 8.61 (till 6th Semester)

Courses

Data Structures and Algorithms

Operating Systems

Computer Networks

Database Management System

DAV Public School

Bhubaneswar, Odisha, India
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Senior Secondary (Class XII) Grade: Percentage: 95.6%

DAV Public School

Bhubaneswar, Odisha, India
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Secondary (Class X) Grade: Percentage: 97.4%

Skills

Languages

C++, Python, JavaScript, HTML.

Libraries & Frameworks

React.js, Express.js, FastAPI, Streamlit.

Tools & Platforms

MongoDB, Node.js, Docker, Git/GitHub.

Projects

Smart-Netfix

Summary

A full-stack internet diagnostic tool built with FastAPI, MongoDB, Streamlit, Python CLI, and Docker for checking connectivity, DNS, speed, and latency.

Mental Health Risk Prediction (Academic Project)

Summary

An academic machine learning project utilizing XGBoost, CatBoost, Optuna, and SMOTE to predict mental health risks from behavioral and demographic data.

Appointment & Leave Management System (Internship Project)

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Summary

A full-stack MERN application developed during an internship for managing appointments and leaves, featuring role-based access and a real-time dashboard.