My Builds.

An Institute of National Importance Website, where I re-innovated on completed frontend and some of old backend of the website, created a custom CMS for the admin to manage the content of the website, resulting in a remarkable 95% performance improvement in rendering, and achieving a flawless 100% SEO and best practice score

Designed and implemented an API and mobile application for an academic project focused on advanced image processing techniques. Integrated arithmetic operations, spatial domain transformations, and frequency domain filtering using convolution-based techniques.

This industry project focused on developing an image processing pipeline to detect and analyze gas burner holes using OpenCV and Hough Transform. It enhanced visibility through contrast stretching, applied segmentation for accurate detection, and extracted key measurements like hole count and size distribution. Masking and filtering refined the analysis, while automated CSV reports enabled efficient data evaluation.

A database management system exploring project on ticketing system of railways, Innovated UI into a macOS clone with subtle animations using popmotion and winbox, learnt about using various ORMs like Prisma, Drizzle, etc., along with direct SQL query execution.

Developed a machine learning system for emotion recognition using ECG signals, extracting time-series features like HRV metrics (RMSSD, SDNN, NNx, CSI, CVI). Implemented and evaluated Decision Tree and Random Forest classifiers to predict emotions such as happiness, anger, and disgust.

A mobile social media chat application which includes features inspired from snapchat and whatsapp, where I learned about real time streaming data to update chat, worked with lottie files for animation and firebase for backend.

Developed facial recognition and traffic sign recognition systems using machine learning and deep learning techniques. For facial recognition, implemented Principal Component Analysis (PCA) for dimensionality reduction and used KNN, LDA, and Logistic Regression models. For traffic sign recognition, applied CNNs and utilized the GTRSB dataset for training. Leveraged OpenCV and PIL for image processing, gaining hands-on experience with real-world data collection and deep learning concepts.

A microservices-based invoicing application with a dedicated Google OAuth authentication service, a Postgres + Redis resource service, and a Next.js dashboard for creating and managing invoices. Automated email notifications through a BullMQ message broker integrated with Zapier, JWT-based authorization across services, and a fully Dockerized local development setup.

A server-side rendered website built for a real educational academy client using Node.js, Express, and MongoDB. Content is dynamically rendered from the database, includes a YouTube-clone tutorial viewer for course videos, and integrates a fully secure RazorPay payment gateway for enrollments. Deployed on Heroku.

A published npm CLI package (@nsvegur/profile) that renders an interactive terminal profile card when run via `npx nsvegur` - complete with styled text, an inline image, and clickable links, built with chalk, inquirer, and terminal-image.

A geolocation-based web app to map and visualize your running or cycling routes, built to explore the browser Geolocation API using the Leaflet mapping library.