Specializing in
AWS, Azure, GCP architecture and deployment
Security frameworks and threat analysis
Docker, Terraform, CI/CD pipelines
Next-gen computing research and development
/education.stack
Academic upgrades logged as system builds and milestones.
Specializing in Cloud Technology and Information Security. Active in hackathons and cybersecurity clubs. Current CGPA: 9.9.
Completed intermediate education focusing on science and mathematics. Grade: 93.9%.
Completed higher secondary education. Grade: 87.6%.
/experience.runbook
Internships and research as ops logs and deployed missions.
Contributing to frontend development, UI/UX enhancements, and full-stack feature implementation using HTML5, CSS3, JavaScript, EJS templates, MySQL, and Express.js.
Coordinated end-to-end placement activities, managed candidate databases, and supported IT solutions integration into placement processes.
Engaged in advanced research on distributed computing and serverless architectures. Implemented XFBench and XFaaS frameworks for Function-as-a-Service environments.
/skills.matrix
Built and deployed a cloud-native multi-cloud orchestration platform with containerized microservices using Docker and infrastructure provisioning via Terraform. Implemented automated background jobs with Celery and Redis for periodic synchronization of cloud resource data from AWS, Azure, and GCP APIs. Designed CI/CD-friendly architecture and production-ready deployments with secure JWT authentication, PostgreSQL-backed services, and scalable FastAPI backend. This project highlights practical experience in infrastructure automation, containerization, service orchestration, and operational reliability.
I built a Software-as-a-Service (SaaS) platform leveraging AI to provide automated business solutions for modern video management. The platform utilizes a robust tech stack, including Next.js 14 for the frontend framework, TypeScript and JavaScript for application logic, and Tailwind CSS for responsive styling. For secure user authentication, it integrates Clerk, while Prisma ORM with Neon DB (PostgreSQL) manages the database. Cloudinary is used for scalable video storage and optimized delivery, and the platform is deployed seamlessly on Vercel. AI is harnessed to automate business workflows and enhance video-related operations, creating an efficient, scalable, and user-friendly solution.
I developed a hybrid cloud-quantum system that seamlessly integrates classical cloud computing with quantum processing to achieve enhanced computational efficiency. The workflow enables interoperability between traditional cloud services and quantum systems, providing secure and scalable solutions. This hybrid architecture is implemented using AWS for cloud infrastructure, IBM Quantum for quantum resources, and Docker for containerization, ensuring flexible deployment and robust integration across platforms.
I developed a comprehensive full-stack educational management system featuring role-based dashboards, integrated AI-powered tools, and bilingual (English/Hindi) support. The platform offers streamlined admin, teacher, and student workflows, including live virtual classes, automated quiz grading, real-time analytics, AI-assisted tutoring, and activity monitoring. The tech stack includes React.js and Tailwind CSS for the frontend, Node.js, Express.js, and Socket.io for the backend, and MongoDB for data storage. Secure authentication is implemented using JWT, with AI functionalities powered by OpenAI API and TensorFlow.js. Translation is enabled via the Google Cloud Translate API, and the system is deployed using Docker and Nginx for scalability and reliability.
I developed XAI Interpret, a hands-on platform for model interpretability that implements state-of-the-art Explainable AI (XAI) techniques using SHAP and LIME. The project provides a complete machine learning pipeline, from data preprocessing and model training to real-time, interactive explanations for individual predictions. Supporting various ML algorithms, the system helps users understand both global and local model behavior, feature interactions, and produces rich visualizations for interpretability. Built for practical use, it’s compatible with Google Colab and supports cloud deployment on Vertex AI, featuring production-ready model persistence, scalable architecture, and comprehensive LaTeX documentation. This solution fosters transparency and trust in machine learning models, making it especially valuable for black-box medical diagnostics and other high-stakes domains.
I built a personal cloud storage system using Docker containers, featuring an interactive user interface for seamless file management. The platform supports file uploading, listing, and downloading functionalities, while Dockerized deployment ensures easy scalability. Secure authentication mechanisms and robust data storage practices safeguard user data, making the system both efficient and secure for personal cloud storage needs
Cross-platform mobile application built with Flutter SDK for sustainable products marketplace, running on both iOS and Android devices.
GitHub Achievements
HackerRank Badges
Python 4⭐(Silver)
SQL 4⭐(Silver)
Problem Solving 2⭐(Bronze)