About

I am Manobharathi Mahendran, a B.Tech in Information Technology graduate from KLN College of Engineering, class of 2026. During my studies, I completed internships as a Java Full Stack Developer at Craitrix Technologies and a Software Developer at Infinity Uniquers, where I worked on HRMS and LMS platforms, built REST APIs, and developed frontend features using React.js and Next.js. My strongest skills include Java, Python, Spring Boot, REST APIs, JPA/Hibernate, Microservices, and full-stack web development with React.js and Next.js. I am currently seeking my first full-time role as a Full-stack Developer.

Experience

1. Java Full Stack Developer Intern

   Craitrix Technologies

   Jun 2026 – Sep 2026

   Developed and maintained backend services in Spring Boot and frontend features in Next.js for a production HRMS platform used across HR operations. Delivered end-to-end features across Background Verification (BGV), Email Templates, and Customer Support modules, streamlining core HR workflows. Performed manual and automated testing with Playwright, identifying and resolving critical bugs to improve application stability.

2. Software Developer Intern

   Infinity Uniquers

   Nov 2024 – Mar 2025 · Madurai, Tamil Nadu

   Built responsive, cross-browser-compatible web applications using HTML, CSS, and JavaScript. Designed a reusable UI component library that standardized interface patterns and reduced development time for new features. Integrated REST APIs into frontend interfaces to enable dynamic data rendering on data-heavy views. Collaborated with a 5-member Agile team, contributing to sprint planning, daily stand-ups, and code reviews via Git/GitHub.

Education

1. KLN College of Engineering

   B.Tech, Information Technology

   2022 – 2026 · Grade: 8.2 / 10

Projects

• PulmoScan AI — Chest X-ray Disease Detection System

  • Python
  • PyTorch
  • TensorFlow
  • Keras
  • Streamlit
  • EfficientNet
  • Grad-CAM

  Built an AI-powered web app that detects 14 lung diseases from chest X-rays using a multi-model deep learning architecture (EfficientNet + TensorFlow/Keras). Added Grad-CAM explainability to generate visual heatmaps highlighting disease-affected regions, and deployed a real-time Streamlit interface for practitioners.

• Plant Disease Detection using CNN

  • Python
  • TensorFlow
  • Keras
  • Streamlit

  Trained a CNN-based model to classify plant diseases from leaf images, achieving over 95% accuracy on the test dataset. Deployed a real-time Streamlit app enabling farmers to upload leaf images and get instant diagnosis with feedback.

• AI Mock Interview System (Career Warmup)

  • Java
  • Spring Boot
  • JavaScript
  • REST APIs

  Built a full-stack mock interview platform with a Spring Boot backend and JavaScript frontend to simulate technical interviews. Designed RESTful APIs for question banks, responses, and session state; added rule-based NLP evaluation for automated feedback.

Certifications

• Java Full Stack Development

  Elysium Academy · 2025

• Research Paper Publication

  IEEE · 2025

• SIH Internal Hackathon

  SIH · 2024

• LeetCode

  LeetCode · 2025

Achievements

• IEEE Research Paper Publication

  2025

  Published peer-reviewed research paper on a deep learning-based application.

• SIH Internal Hackathon

  2024

  Selected participant representing the college at a national-level hackathon — two consecutive years.

• Java Full Stack Development

  2025

• LeetCode