A clean and interactive web app that visualizes and compares sorting algorithms in real-time for educational and demonstration purposes.

A SageMath implementation of Edwards-Curve Digital Signature Algorithm (EdDSA), featuring secure key generation, signing, and verification. Focused on Cryptographic Primitives and highly efficient, scalable algorithms.

Written as part of a research project at the University of North Texas, this report offers insights into the evolving landscape of pathfinding and serves as a reference for developers and researchers working in fields such as robotics, networking, and AI-based navigation systems..

A Minimum Spanning Tree with 30 nodes and vertices for optimizing Tokyo's railway station network using Prim's algorithm. This project uses both C++ and Python with run time analysis and manual calculations of MST.

Comparative analysis of various sorting algorithm efficiency in C++, Java, and Python

This repository contains the "ABCU Course Scheduler" project, developed to assist academic advisors at ABCU in planning and advising on course schedules. The project focuses on efficient data handling, using appropriate data structures to ensure courses are taken in the correct sequence. The experience emphasized the importance of choosing the righ

This project implements an optimized version of the Quicksort algorithm in C++, using a randomized pivot selection (first or last index during the partition). Additionally, the project features a manual analysis of the algorithm's running time in the worst-case and average-case scenarios.

Undertook the RSA Factoring Challenge, employing algorithmic techniques to factorize numbers into prime factors, exploring both standard and advanced tasks.

A tool to time algorithms and measure their efficiency and complexity

A comprehensive performance analysis of N log N sorting algorithms (Heap, Tim, Intro, Merge, Quick) implemented with hybrid MPI and OpenMP. Explores algorithm complexity, multi-threading (1-16 threads), multi-core (1-4 cores), and scalability on large datasets, with detailed performance graphs.