Hi, I'm Vaibhav 👋
Third-year B.Tech Computer Science student with hands-on expertise in Full-Stack Development (MERN) and Machine Learning.
VV

Available — Open to internships and software engineering opportunities

About

Delivered production-ready projects including a feature-rich fitness tracker (FitPal), brain tumor detection system using PyTorch and BRATS dataset (NeuroVision), OSINT-based facial identification, and equipment parameter analytics. Proficient in React.js, Node.js, Express, MongoDB, Python, REST APIs, Git, and modern tooling.

Education

V

Vellore Institute of Technology

2023 - 2027
B. Tech in Computer Science Engineering
A

Aster Public School

2022 - 2023
CBSE Boards 12th (PCM)

Skills

Python
Java
C++
JavaScript
SQL
ReactJS
NextJS
NodeJS
ExpressJS
MongoDB
PyTorch
TensorFlow
HTML5
CSS3
Git
My Projects

Check out my latest work

I've worked on a variety of projects, from web applications to machine learning systems. Here are a few of my favorites.

Urban Grocer

Urban Grocer

A full-featured grocery delivery platform with real-time inventory, cart management, and seamless checkout experience. Built with a modern tech stack and deployed on Vercel.

React
Node.js
Express
MongoDB
Tailwind CSS
Source
Website
FitPal — Fitness Tracker

FitPal — Fitness Tracker

Developed FitPal — track nutrition, calculate BMI, suggest exercises based on goals, and visualize progress via graphs. Features a responsive UI and integrated backend services.

MongoDB
Express
React
Node.js
Tailwind CSS
GSAP
Source
Website
Secure-OSINT-FaceID

Secure-OSINT-FaceID

OSINT-driven facial identification system developed under the EPICS framework. Integrates Computer Vision with Open-Source Intelligence to identify individuals and automatically trigger web-scraping for unrecognized faces, with dedicated modules for consent management and audit logging.

Python
MediaPipe
OpenCV
PyTorch
TensorFlow
Keras
scikit-learn
Selenium
BeautifulSoup
Source

NeuroVision — Brain Tumor Detection

Developed a machine learning model to process .nifty MRI scans and detect brain tumors using the official BRATS dataset. Implemented preprocessing pipeline with NiBabel, NumPy, and OpenCV.

Python
PyTorch
TensorFlow
NiBabel
NumPy
OpenCV
Source

Equipment Parameter Insights

A powerful hybrid application (Web + Desktop) for analyzing, visualizing, and reporting chemical equipment data. Features automated reporting and interactive data charts.

Django + DRF
React + Chart.js
Pandas
PyQt5
ReportLab
Source
Let's Connect

Open to Opportunities

I'm actively looking for internships and collaborative projects. Whether it's a full-stack application, a machine learning system, or anything in between — let's build something great together.

Get in TouchView GitHub
LinkedIn
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