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.

Multi-class classification model predicting news article popularity from 39K Mashable articles. Uses strategic class balancing (1/3, 1/4, 1/5, 1/6, 1/7 distribution) and feature selection to handle severe imbalance. Final SVM achieves 0.65 accuracy, 0.25 F1-macro.