Projects
Portfolio-Website-Builder
The Portfolio-Website-Builder is a robust application designed to streamline the creation of personalized portfolio websites. By leveraging AI-assisted features and a user-friendly interface, it empowers users to showcase their skills effectively.
AADI
AADI is a microservice-based project designed to enhance order management through innovative features such as geofencing and capacity awareness. The project leverages a robust tech stack, including JavaScript, TypeScript, and Python, to deliver a seamless experience across customer and admin portals.
AdaptiveNPC
AdaptiveNPC is a monolithic application utilizing a component-based architecture, developed in C# with Unity. The system comprises 66 files and integrates several advanced features, including a Memory System and Smart Responses, which present unique engineering challenges in NPC behavior modeling.
VisionAPI
VisionAPI is a streamlined project developed entirely in Python, showcasing a monolithic architecture. Its simplicity allows for rapid deployment and ease of maintenance, making it an ideal solution for straightforward API needs.
Hear-It
Hear-It is a mobile application designed to enhance the social experience of hearing impaired individuals. By incorporating keyword recognition and a social communication aspect, it aims to improve users' confidence and security in their surroundings.
Two-pass-assembler-loader
The Two-pass-assembler-loader project is a streamlined solution developed entirely in Python. Its monolithic architecture ensures simplicity and ease of maintenance, making it an efficient tool for assembly language processing.
BitTorrent
BitTorrent is a terminal-based application that implements the P2P file sharing protocol, enabling users to share files efficiently. It features a tracker creation capability and peer connectivity, enhancing the overall file sharing experience.
GAN-and-VAE-networks-on-MNIST-dataset
The project implements Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE) on the MNIST dataset using Python. It showcases the ability to simulate complex neural network architectures, providing valuable insights into generative modeling.
Min-Heap-and-Red-black-tree-implementation-for-City-Building-Project
This project involves a layered monolithic architecture implemented entirely in Java, focusing on the development of Min-Heap and Red-Black Tree data structures. The project presents engineering challenges related to data management and performance optimization, which were addressed through careful design decisions.
Twitter-Engine
The Twitter-Engine project is a serverless application developed in F#. It employs a RESTful architecture and integrates various libraries such as Akka.FSharp and DotNetty to handle real-time updates and user interactions efficiently.