Software Engineering Portfolio
Finance Tracking System
Technologies: MERN Stack, MongoDB, Express, React, Node.js, JWT, Clerk, TypeScript, CSS
GitHub Repository: Link to Repository
- Engineered a personal finance tracking app with MERN stack, addressing expense, income, and budget management while securing user access with JWT and Clerk authentication
- Designed an intuitive React and TypeScript UI for adding, updating, and deleting expenses, optimizing user experience, and leveraging MongoDB for data storage
PharmaCutieCal: Drug Side Effect Analysis
Technologies: React, Flask, MongoDB, Machine Learning, Hyperparameter Tuning, Random Forest Classification
GitHub Repository: Link to Repository
- Spearheaded the development of a React-based application with a user-friendly UI for capturing medical history and accessing records, integrating a drug input feature and utilizing MongoDB for data storage
- Implemented a Machine Learning model trained on a dataset of 250k drugs and their side effects to predict potential side effects from user data, developing a Flask-based API for seamless application integration
Content Management System
Technologies: Spring boot, Java, React, MongoDB, Object Oriented Programming
GitHub Repository: Link to Repository
- Engineered a Spring Boot API integrated with a React UI to facilitate user access and quiz creation, leveraging a Canvas-like CMS and implementing role-based access control to manage users, courses, and terms
- Orchestrated seamless interaction between services via Fetch calls to optimize data exchange, augmenting system functionality, and performance while implementing storage of user data within MongoDB
Malware Detection and Web Security
Technologies: C#, PHP, HTML, Machine Learning
GitHub Repository: Link to Repository
- Spearheaded the development of a C# application for system scanning, integrating machine learning models, achieving a 98% accuracy rate in identifying malware
- Engineered a web browser extension using HTML and PHP, integrating a machine learning model to identify and flag malicious URLs with a 96% precision rate, providing users with real-time security alerts