Vinner
Resume โ†“
Let's BUILD some tech.
$ docker build -t vinner .$ git push origin main$ npm run deployโ–Œ
Vinner
Vinner's photo

About

I build end-to-end web applications and research satellite-based disaster detection. Next.js by day. Docker and AWS by night.

Delhi, India ยท Open to work

MCA ยท Christ University

Currently Learning

Docker

Containerizing personal projects

GitHub Actions

Building CI/CD pipelines

AWS

Cloud Practitioner prep

Linux

Shell scripting & server management

Roadmap

Tutedude DevOps Course

๐ŸŽฏ Goal: DevOps Internship ยท Late 2026

Tech Stack

โš›๏ธReact
โ–ฒNext.js
๐ŸŸฆTypeScript
๐ŸPython
๐ŸŽจTailwind
๐Ÿ‹Docker
โ˜๏ธAWS
๐Ÿ™Git
๐ŸงLinux
โš›๏ธReact
โ–ฒNext.js
๐ŸŸฆTypeScript
๐ŸPython
๐ŸŽจTailwind
๐Ÿ‹Docker
โ˜๏ธAWS
๐Ÿ™Git
๐ŸงLinux
โš›๏ธReact
โ–ฒNext.js
๐ŸŸฆTypeScript
๐ŸPython
๐ŸŽจTailwind
๐Ÿ‹Docker
โ˜๏ธAWS
๐Ÿ™Git
๐ŸงLinux
โš›๏ธReact
โ–ฒNext.js
๐ŸŸฆTypeScript
๐ŸPython
๐ŸŽจTailwind
๐Ÿ‹Docker
โ˜๏ธAWS
๐Ÿ™Git
๐ŸงLinux

Projects

โ†—
Gym Management System
Gym Management Systemโ†—

Full-stack SaaS-style fitness management platform for personal trainers. Features real-time chat, Google Calendar API integration, role-based authentication, dynamic workout planner, performance charts with E-1RM calculator, and meal plan management.

E-Commerce Platform
E-Commerce Platformโ†—

Full-stack e-commerce platform with separate Admin, Seller, and Buyer roles. Designed in Figma before implementation. Built with Node.js, Express and EJS templating with raw PostgreSQL queries. Features bcrypt authentication, product management, cart and order functionality.

ANPR System
ANPR Systemโ†—

Automated Number Plate Recognition system integrating YOLO object detection and PaddleOCR. Achieved 80% accuracy across diverse lighting and weather conditions with 20% improvement in data throughput over manual methods.

Flood Detection & Severity Mapping โ€” IEEE Research
Flood Detection & Severity Mapping โ€” IEEE Researchโ†—

IEEE accepted research on satellite-based flood detection using deep learning. Trained a U-Net CNN on Sentinel-1 SAR imagery achieving 83% recall optimized for disaster response. Generated probabilistic severity maps for the Ganga floodplain.