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• Engineered an end-to-end Explainable AI (XAI) application for retinal scan classification utilizing transfer learning on a fine-tuned ResNet50 architecture.
• Implemented Score-CAM techniques to generate visual heatmaps, ensuring AI diagnostic predictions were interpretable and transparent for medical use cases.
• Developed a server using Python and Flask to serve machine learning inference, supported by a PostgreSQL database for reliable data management.
• Built a responsive, type-safe user interface utilizing React, TypeScript, and React Query for highly efficient server-state management
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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DataStory turns any CSV into a visual story your audience can actually understand. Upload data, pick your audience — Business, NGO, Student, or Social Media — and instantly get charts, AI insights, and a narrative in the right tone.
🔗 Live App: gloss-pink-92515363.figma.site
Built with Figma Make + Supabase.
Interview Prep : Full-Stack SaaS for Tech Interview Preparation
AI Chrome Extension for Instant Cover Letter Generation (Job Jolt)
I built Job Jolt, an AI-powered cover letter generator designed to help users create tailored job applications directly from real job listings in seconds.
The product combines a Chrome extension with a backend web application to streamline the entire workflow. Users can visit a job listing on platforms like LinkedIn, extract relevant job data with a single click, and instantly generate a customized cover letter powered by AI.
On the frontend, I developed a React-based Chrome extension that injects seamlessly into job listing pages. The extension handles data extraction, sanitization, and formatting before securely sending structured requests to the backend.
On the backend, I built a Flask-based system integrated with OpenAI to generate high-quality, context-aware cover letters in under 20 seconds. The system was designed for speed and reliability, making it one of the fastest solutions in its category.
A strong focus was placed on security and robustness. I implemented API key validation, token-based authentication, rate limiting, and secure password handling to ensure the platform could scale safely while protecting user data.
The result is a smooth, end-to-end user experience that removes friction from the job application process and demonstrates how AI can be integrated directly into real-world workflows.
This project highlights my ability to combine frontend UX, browser extensions, and AI-powered backend systems into a cohesive and high-performance product.
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