About Me

Pranathi Rallabandi

Pranathi Rallabandi

Hi! I am a passionate tech explorer, pursuing my studies in Computer Science and Engineering with a deep focus on AI/ML. I bridge the gap between complex algorithmic systems (like Graph Neural Networks) and production-ready full-stack applications.

9.0 B.Tech GPA
1 Published Patent

Education

2023 - Present
Bachelor of Technology in Computer Science & Engineering

Specialized in Artificial Intelligence and Machine Learning

NRI Institute of Technology | GPA: 9.0

Achievements & Certifications

  • 2nd Prize – Innovarix, Ameya’25 (SRM University-AP) for Green Circuit
  • Finalist – DataVortex SkyIntellect Hackfest 2025 (KL University) for MARG AI
  • Udemy Certification: Full-Stack Web Development (HTML, CSS, JS, Node.js, React, PostgreSQL, Web3, DApps)

Technical Skills

Languages

Python JavaScript Java HTML5 CSS3 SQL

AI / ML & Vision

PyTorch Graph Neural Networks (GCN/GAT) OpenCV Knowledge Graphs NetworkX TensorFlow Lite Google ML Kit XAI (Explainable AI) LBPH Face Recognizer

Full-Stack & Cloud

React.js Vite Tailwind CSS Node.js Express.js MongoDB Atlas PostgreSQL AWS S3 Firebase Google Drive API Cloudinary Web Push

Core & Other

Flutter JWT Authentication NFC-based tracking Tkinter GUI Git & GitHub

Languages Spoken

English Hindi Telugu

Featured Projects

A selection of research innovations, full-stack systems, and AI modules.

Published Patent
Patent App: 202541086955 (2025)

GNN-Based Explainable Educational Recommendation System

Designed and implemented a knowledge graph-driven educational recommendation system integrating learner goals, concept relationships, and prerequisite/resource dependencies.

  • Built a Graph Neural Network-based framework (GCN/GAT) to perform multi-hop reasoning on learner-resource graphs and generate personalized resource recommendations.
  • Added an explainability layer for interpretable recommendation paths and a feedback-based graph update mechanism to continuously improve recommendation quality.
Python PyTorch GCN GAT Knowledge Graphs NetworkX XAI
Web & Mobile System
Active Platform

Say Whaat – Donation Tracking & Logistics Management

An end-to-end donation tracking and distribution platform featuring a React portal for donors/admins and a Flutter app for field staff, ensuring transparency from registration to delivery.

  • Developed an offline face verification pipeline in the Flutter app using Google ML Kit and MobileFaceNet (TensorFlow Lite) for secure authentication in low-connectivity zones.
  • Implemented NFC-based item tracking, AWS S3-backed delivery proofs, real-time push notifications, and verified proof-of-delivery workflows.
React.js Flutter Node.js TFLite Google ML Kit AWS S3 MongoDB NFC
Web Application
Ongoing

Frontier ESPI – Research Journal Management Portal

Built an end-to-end journal management system permitting authors to submit manuscripts and editors to manage submissions and peer review processes from a single dashboard.

  • Integrated automated email notifications with Nodemailer to notify users of manuscript status updates instantly.
  • Integrated Google Drive API for secure document storage and streamlined document flows for editors.
React.js Vite Tailwind CSS Node.js Express.js MongoDB Atlas Google Drive API
Portal Platform
Deployed

College Website Management System

Implemented a role-based content management system for administrators and department heads to manage events, notices, faculty profiles, galleries, and institutional info.

  • Developed secure JWT authentication, cloud-based media handling with Cloudinary, and real-time updates.
  • Created dedicated control panels optimized for department-level information distribution.
React.js Vite Tailwind CSS Node.js MongoDB Atlas Cloudinary Google Drive API
Computer Vision
Completed

Smart Attendance System with Real-Time Face Recognition

Developed a real-time attendance tracking system using computer vision-based face recognition to automate student identification and attendance logging.

  • Built recognition workflow with OpenCV and LBPHFaceRecognizer, covering dataset collection, training, live detection, and real-time marking.
  • Designed a clean Tkinter GUI for admin registration and student attendance management, logged directly into CSV formats.
Python OpenCV Tkinter LBPH Recognizer CSV Logging