Aditi Kumari

Full Stack Engineer with less than a year in React, Node.js, Python, and Machine Learning.

National Institute of Technology, Patna

Patna, Bihar, India

Since April 25, 2026

About

Aditi Kumari is a highly motivated Bachelor of Technology student specializing in Computer Science and Engineering at NIT Patna. She possesses strong full-stack development skills, with proficiency in React, Node.js, Python, and cloud platforms like AWS. Her projects demonstrate an ability to build scalable applications, implement secure authentication, and optimize performance, showcasing her problem-solving abilities and passion for technology.

Top Skills

PandasMongoDBPythonRestful ApiScikit Learn

Skills

C++C++JavaJavaScriptPythonGithubPostmanPower BIReactjsExpress.JsNode.JsTailwindSQLMongoDBObject Oriented ProgrammingArtificial IntelligenceMachine LearningReactjsExpress.JsNode.JsTailwind CssAWSMongoDBPythonScikit LearnPandasFlaskReact.jsSQLRestful Api

Education

National Institute of Technology, Patna

B.Tech. · Computer Science and Engineering

August 1, 2022 – June 30, 2026

Bihar School Examination Board, Patna, Bihar

Intermediate

June 1, 2021 – May 31, 2021

Central Board of Secondary Education

Matriulation

June 1, 2019 – May 31, 2019

Projects

AudioZen

January 1, 2024 – April 1, 2026

Developed a full-stack music streaming platform enabling seamless music playback, playlist management, and role-based authentication, ensuring a smooth user experience across devices. Implemented JWT authentication, reducing unauthorized access by 100% and ensuring secure user sessions with encrypted tokens and session management. Designed a scalable playlist system supporting thousands of users, with features like creation, modification, and playback to improve personalization. Developed an Admin Panel for managing CRUD operations with access control, improving workflow efficiency by 40% and enabling track moderation. Engineered a RESTful API, reducing response times by 40% and handling daily API requests efficiently. Deployed on AWS, enabling auto-scaling capabilities, load balancing, and maintaining 99.9% uptime, ensuring reliability under heavy traffic.

View Project

BookHive

January 1, 2024 – April 1, 2026

Built a personalized book recommendation system, increasing recommendation accuracy by 25% using Collaborative Filtering to enhance user satisfaction. Optimized similarity-based recommendations with Cosine Similarity and Matrix Factorization (SVD, ALS), ensuring precise book suggestions for diverse user interests. Processed and analyzed 50+ book records using Pandas and NumPy, improving dataset processing speed and reducing computational overhead. Designed a Flask-based API, enabling real-time recommendations for users by efficiently serving machine learning predictions with low latency. Integrated the backend with a React.js frontend for a smooth and interactive user experience, reducing client-server latency by 30% through API optimizations. Deployed on Heroku with enhanced database queries, indexing strategies, and caching mechanisms.

View Project

Certifications

Leetcode

Unknown

April 1, 2026 – Present

GeeksForGeeks

Unknown

April 1, 2026 – Present

Participation Certification in ByteVerse

Hackslash Club

April 1, 2024 – Present

Participation Certification in Pitchtember

Incubation Centre

November 1, 2023 – Present

Key Strengths

Demonstrated foundational understanding of full-stack development through academic projects (AudioZen, BookHive) using React.js, Flask, and SQL.
Exposure to cloud deployment concepts with AWS (auto-scaling, load balancing) and Heroku (database optimization, caching) in project contexts.
Experience with machine learning concepts (Collaborative Filtering, Cosine Similarity, Matrix Factorization) and data processing using Pandas and NumPy.
Implemented key system design elements such as JWT authentication, RESTful APIs, and scalable playlist systems in projects.
Strong academic background with a B.Tech. in Computer Science and Engineering from a reputable institution (NIT Patna).

Cultural & Operational Fit

Cultural Fit Analysis

Based on the psychometric test score of 0/500, there is no data to assess cultural fit aspects such as work attitude, stress handling, or team collaboration. Data is insufficient.

Soft Skills & Operational Fit

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