My profile lists four certifications and training credentials, spanning cloud architecture, data analytics, MongoDB, and networking.
I earned the AWS Academy Graduate - Cloud Architecting - Training Badge from Amazon Web Services (AWS) in Oct 2025.
I completed the Tata - GenAI Powered Data Analytics Job Simulation through Forage in Aug 2025.
I completed MongoDB Basics for Students from MongoDB in Jun 2025.
I completed Networking Basics from Cisco in Oct 2024.
I designed an AI-powered interview and ATS resume preparation platform to help job seekers prepare for interviews and optimize resumes. It combines an NLP-based resume parser and scoring engine, voice- and text-based mock interviews, REST APIs for interview and resume analysis, and PostgreSQL-backed data management for personalized feedback. I evaluated 200+ sample resumes and achieved up to 88% keyword-match accuracy.
I developed a full-stack AI assistant that integrates OpenAI GPT and Google Gemini so users can compare responses from multiple large language models in one interface. I built secure REST APIs with FastAPI, added user authentication and persistent chat history, and created a responsive React.js frontend.
I developed a Community Kitchen web platform to reduce food waste by redistributing surplus food locally. It supports user coordination and food postings, with basic analytics.
I developed MediScan, an AI-based disease analysis system that predicts potential diseases from user-entered symptoms. I collected and preprocessed symptom datasets, trained and evaluated classification models using Python, NumPy, Pandas, and Scikit-learn, and built a simple interface for entering symptoms and viewing predictions. The project developed my skills in machine learning, data handling, model development, and application design.
I designed an electric micro-mobility hub concept combining EV charging, parking, and shared e-bikes, with a focus on sustainability and reducing congestion.
I built an AI-assisted learning platform for students with Autism, ADHD, and Dyslexia. It uses adaptive quizzes and data-driven insights to provide personalized learning paths.
I developed XEDLAB Clinical, a full-stack AI medical report analyzer that processes PDF, image, and text reports using OCR, NLP, machine learning, and RAG. It includes an 11-class report classifier, deterministic lab-value validation and abnormality detection, and RAG-based question answering with source-page citations. I added JWT authentication, rate limiting, CORS, and privacy-safe logging; built the backend with Python and FastAPI; and deployed the application on Render. I focused on improving the reliability of AI-generated medical insights by combining deterministic validation with LLM-based reasoning.