Niroop A H

Dynamic Software Developer Intern at Moodys Ratings, adept in full-stack development and API integration. Successfully constructed secure, scalable RESTful APIs using Angular and Spring Boot, enhancing microservices communication. Proficient in Git and JIRA, demonstrating strong problem-solving skills and a commitment to modular enterprise application design.

• Introduction to Web Development
• Git and GitHub
• Developing Front-End Apps with React

Anonymous Complaint Box :

• Developed a secure web-based complaint system enabling users to submit anonymous complaints while ensuring privacy using SHA-256 and bcrypt hashing.
• Built and integrated AI-powered complaint summarization using Hugging Face models (BART) via a Flask microservice for efficient administrative review.
• Implemented sentiment analysis and tag-weighted prioritization using BERT to automatically rank complaints by urgency.
• Enabled real-time email notifications to admins using Nodemailer for new complaint alerts.
• Designed a responsive and user-friendly UI with React.js and Tailwind CSS; deployed the full-stack application on Netlify.
• Ensured smooth frontend-backend communication with RESTful APIs and maintained MongoDB for persistent complaint storage.

Meetly - Video Conferencing Application:

• Developed a modern, responsive web platform using Next.js and Shadcn/ui, focusing on accessibility and seamless user experience.
• Implemented Clerk authentication to support secure sign-in/sign-up flows, role-based access control, and social login options.
• Integrated Stream.io SDKs to enable real-time video calling, messaging, and collaborative meeting features within the application.
• Employed server-side rendering and dynamic routing in Next.js to enhance performance and SEO readiness.
• Optimized for scalability and responsiveness across devices, with deployment and CI/CD powered by Vercel.

Catch and Crunch Game:

• Designed and developed an interactive educational game using Python, OpenCV, and MediaPipe to teach children how to distinguish between eatable and non-eatable objects.
• Implemented real-time object detection and gesture tracking to create an engaging and intuitive learning experience.
• Integrated ClearML for experiment tracking and performance monitoring to iteratively optimize gameplay accuracy and responsiveness.
• Focused on promoting food safety awareness and introducing basic computer vision concepts through playful interaction.
• Deployed the project on the CV Zone platform, making it freely accessible for educational use and community engagement.