I work on Artificial Intelligence, Machine Learning, and Cyber Security. I like building things that actually work, figuring out things as I go, including end-to-end AI prototypes and full-stack web applications. I’m good at taking machine learning models and fitting them into real systems so they can scale. What excites me most is creating smart, secure, and efficient solutions that mix solid software engineering with AI in practical, useful ways.

Master's in Computer Science
August, 2024 - December, 2025Master's in Computer Science

B.Tech in Computer Engineering
June, 2020 - May, 2024B.Tech in Computer Engineering

Full Stack Developer
Dec, 2023 - May, 2024Full Stack Developer

Full Stack Developer Intern
May, 2023 - Jun, 2023Full Stack Developer Intern

A Python-based MCP server built with FastMCP that connects internal knowledge bases to Claude or other MCP-capable LLMs, allowing employees and tools to search, retrieve, and query internal documents in a structured, auditable way.

This is a Python-based Face ID system that can register multiple users, and later verify a person using facial similarity. It uses a Siamese Neural Network implemented in PyTorch and OpenCV for real-time webcam face capture.
Real-time rodent tracking for Open Field Assay using YOLOv8. Faster and lighter than DeepLabCut, and a free alternative to EthoVision. Supports arena calibration, trajectory mapping, speed metrics, center-zone analysis, and heatmap/annotated video outputs.

A small project that visualizes GPT tokenization and token usage across prompts and responses. The repository contains a Next.js frontend and a lightweight Python backend used to analyze and serve tokenization information.