A comprehensive web application for exploring and analyzing Cantina Royale NFT collections, character stats, weapons, and game data. Built with Next.js and TypeScript.

Comprehensive collection of algorithm exercises covering graph theory, dynamic programming, divide & conquer, and backtracking with complete Python implementations and complexity analysis.

A comprehensive Python library for managing Object-Centric Event Data (OCED), providing a flexible framework for modeling complex business processes where events can involve multiple objects with rich relationships and attributes.

A multi-stage deep learning pipeline combining DCGAN, SRGAN, and dual-discriminator architectures to generate high-quality, unique digital artwork for NFT collections with style blending and super-resolution enhancement.

A location-based marketplace Android application that allows users to buy and sell items with AI-powered image recognition and real-time chat functionality.

Peer-to-pool NFT lending protocol with lottery-based funding. Borrowers collateralize NFTs to create lotteries, lenders purchase tickets to provide liquidity. Zero liquidation risk - loan repayment returns NFT, default triggers random winner selection among ticket holders.

SDN performance analysis framework comparing network topologies using Mininet simulation, Ryu controller, and D-ITG traffic generation to identify bottlenecks and optimize network capacity.

A comprehensive implementation of Bitcoin address clustering using multiple heuristic conditions for blockchain analysis and chain analysis applications.