• Email: Email
• LinkedIn: Neeraj Komatishetti
• Portfolio: Neeraj Komatishetti

I'm a computer science student who is really into technology and innovation. I've good expertise in Full Stack development, a tech nerd, and I love figuring out tricky problems. I'm always looking to collaborate!

• B.Tech: 2022 - 2025
  • B.Tech in Computer Science Engineering from TKR College of Engineering & Technology at Meerpet, Rangareddy(D), Hyderabad.
• Diploma: 2019 - 2022
  • Completed Diploma in Computer Science from TKR College of Engineering & Technology at Meerpet, Rangareddy(D), Hyderabad, with 8.4 CGPA.
• SSC: 2019
  • Completed Secondary Education from Krishnaveni High School, Balkonda, Nizamabad, with 9.8 GPA.

1. Learn Complete Python in Simple Way, from Udemy

• Languages: Python, Java, C, C++, JavaScript, TypeScript, SQL
• Databases: PostgreSQL, MongoDB, Prisma, Supabase
• Backend: Node.js, Express.js, Django, HONO, Cloudflare Workers
• Frontend: HTML5, CSS3, React, Next.js, Vite
• Full-stack: MERN (MongoDB, Express, React, Node) stack; Next.js + TypeScript
• Data & ML: Pandas, NumPy, SciPy, Matplotlib, TensorFlow, Machine Learning
• Dev tooling & practices: Git, Docker, VS Code, PyCharm, Jupyter, Containerization, REST APIs, JWT Authentication, Deployment
• Concepts: Data Structures & Algorithms (DSA), Project architecture, Scalable code organization

• DonateOS(overseas) is a platform built for Registering Donations to foreign countries.
• Developed using TypeScript and NEXTJS for frontend
• HONO, Cloudflare workers for backend
• Uses Postgres as the Primary DB
• And uses Supabase Storage for storing images

• Developed a full-stack fintech app using Node.js, MongoDB, and Vite with JWT-based authentication.
• Enabled secure money transfers, real-time balance updates, and transaction history tracking.
• Architected modular REST APIs and integrated frontend/backend with environment-based routing.
• Containerized the app using Docker for seamless cross-platform deployment.
• Designed for fast local setup and scalable prototyping of financial services.

• Built a full-stack Todo application using Node.js, Express, and React with custom styling and responsive UI.
• Implemented CRUD operations, user-friendly task management, and dynamic state updates.
• Deployed on Vercel with optimized frontend/backend integration for fast performance.
• Designed for scalability and clean code structure—ideal for showcasing full-stack proficiency

Developed a machine learning model to predict digits from the MNIST dataset, a large database of handwritten digits. This project involved:

• Data Preprocessing: Normalizing and preparing the dataset for training.
• Model Training: Using TensorFlow to build and train a neural network.
• Evaluation and Optimization: Assessing model performance and fine-tuning hyperparameters to improve accuracy. This project enhanced my understanding of machine learning concepts and practical implementation using Python and TensorFlow.

1. English
2. Hindi
3. Telugu