3rd Year Computer Science Student
AI • Reinforcement Learning • Simulation
I design and build simulation-driven intelligent systems with a strong focus on machine learning, reinforcement learning, and control under uncertainty. My interests lie in developing robust, scalable, and experiment-driven software systems.
Currently exploring AI control systems, Unreal Engine–based simulations, and learning-based autonomy.
Some of my core projects are maintained in private repositories during active development and experimentation. Public demos, documentation, or selective releases will be shared once the systems reach a stable stage.
Industry-relevant projects demonstrating experience in machine learning, computer vision, and software engineering, with an emphasis on practical implementation and real-world problem solving.
Tags: Computer Vision • Deep Learning • Full-Stack AI • AgriTech
AI-powered livestock management system that identifies Indian cattle breeds using image recognition, with real-time detection, multilingual support, and a RAG-based advisory chatbot.
Tags: Machine Learning • Data Analysis
Predictive machine learning model for pharmaceutical MRP, demonstrating data processing, training, and performance evaluation.
Tags: Software Tooling • Interactive UI • Client-Side Application
A web-based repository structure visualizer that converts JSON folder trees into an interactive, searchable hierarchy with advanced filtering controls.
Tags: Rule-Based System • Conversational UI • Frontend Engineering
Rule-based chatbot application built with React 18, TypeScript, and Vite, offering a modern UI, theming, animations, and persistent conversations.
Tags: UI Engineering • Web Application • Conversational AI • AgriTech
An interactive AgriTech dashboard showcasing agricultural monitoring workflows, featuring a responsive UI and a conversational AI assistant.
Tags: Programming Fundamentals
A clean implementation of the classic game demonstrating core logic, state management, and user interaction.
Advanced projects involving simulation-based control and reinforcement learning are currently under active development in private repositories.
Building systems that learn, not just run.