Projects
Pelvix AI 🤖
A modern full-stack AI chatbot with personality, powered by DeepSeek-R1 and featuring AI image generation, GSAP animations, and real-time chat capabilities.
X-Bird - AI Tweet Reply Generator
Chrome extension that generates intelligent, contextual tweet replies using Hugging Face's Qwen2.5-72B model with multiple mood options and brainrot intensity control.
RAG Application System
A comprehensive Retrieval-Augmented Generation system that integrates external knowledge retrieval with large language models for enhanced AI responses.
Snake's & The Golden Apple
A competitive, AI-driven game where two snakes learn to navigate, collect food, and avoid collisions using Deep Q-Learning.
Cybur
Cybur is a Loadable Kernel Module (LKM) designed to detect and prevent ARP Poisoning Attacks by intercepting ARP packets and validating their authenticity.
Image Super-Resolution GAN
Generates high-quality, photo-realistic images from low-resolution inputs using a Super Resolution GAN.
Neural Black - Brain Tumor Diagnosis System
A comprehensive system for brain tumor detection, classification, and diagnosis using state-of-the-art Deep Learning techniques.
Third Eye - Intrusion Detection System
A hybrid intrusion detection system with a firewall that leverages Machine Learning to analyze network traffic and detect intrusions.
Malware Prediction
Uses Machine Learning to predict whether a portable executable is malware or at risk of being attacked.
Detailed Project Descriptions
Pelvix AI 🤖
Pelvix AI is your digital best friend powered by AI - a modern, full-stack chatbot with personality built with Next.js 15 and React 19. Features include intelligent chat powered by DeepSeek-R1 via Pollinations AI, high-quality image generation with /imagine commands, smooth GSAP-powered animations, and a warm, friendly personality. The application includes real-time chat functionality, custom dark themes, robust error handling, and is optimized for performance and responsiveness across all devices.
X-Bird - AI Tweet Reply Generator
X-Bird is a Chrome extension that generates smart, contextual tweet replies on X.com using AI. Powered by Hugging Face's Qwen2.5-72B-Instruct model (Alibaba's 72B parameter model), it features multiple mood options (Auto, Savage, Supportive, Funny, Professional, Casual), adjustable brainrot intensity control (0-100), intelligent tweet filtering for high-engagement content, secure API key storage, and seamless UI integration with Twitter's interface.
RAG Application System
RAG Application is a comprehensive Retrieval-Augmented Generation system that combines the power of large language models with external knowledge retrieval. This system enhances AI responses by incorporating relevant information from external databases, significantly improving accuracy and reducing hallucinations. The architecture includes vector embeddings, semantic search capabilities, and intelligent knowledge integration for contextually relevant responses.
Snake's & The Golden Apple
Snake's & The Golden Apple is a competitive, AI-driven game where two snakes learn to navigate, collect food, and avoid collisions using Deep Q-Learning. This project demonstrates reinforcement learning in a dynamic environment, showcasing how agents evolve their strategies over time.
Cybur
Cybur is a Loadable Kernel Module (LKM) designed to detect and prevent ARP Poisoning Attacks. It intercepts ARP packets, validates their authenticity, and cross-references them with a dynamically maintained DHCP snooping table to secure the ARP cache.
Image Super-Resolution GAN
Image Super-Resolution GAN employs a Super Resolution Generative Adversarial Network to convert low-resolution images into high-quality, photo-realistic outputs.
Neural Black - Brain Tumor Diagnosis System
Neural Black - Brain Tumor Diagnosis System is an end-to-end solution for detecting, classifying, and diagnosing brain tumors. It leverages advanced Deep Learning methods to achieve high diagnostic accuracy.
Third Eye - Intrusion Detection System
Third Eye - Intrusion Detection System integrates a firewall with Machine Learning algorithms to analyze network traffic and detect potential intrusions, enhancing overall network security.
Malware Prediction
Malware Prediction utilizes Machine Learning techniques to assess portable executable applications, predicting whether they are malware or at risk of being attacked.