Howdinn

Howdinn is an emotional well-being platform that leverages AI-powered sentiment analysis to provide actionable insights into users’ emotions. I developed a machine learning model to classify user input and implemented an intuitive interface for better user engagement. The project demonstrates the potential of technology in addressing mental health challenges through innovation and data-driven analysis.

Tools & Technologies: Python, TensorFlow, Natural Language Toolkit (NLTK), Flask.

Coral Vision Project

The Coral Vision Project focuses on using computer vision to monitor and analyze coral health. I developed algorithms that processed underwater imagery to identify signs of coral degradation. This project combined environmental sustainability with technological innovation, showcasing how AI can contribute to ecological preservation.

Tools & Technologies: Python, OpenCV, TensorFlow, Matplotlib.

Home Automation System

The Home Automation System project showcases my ability to design and implement a comprehensive, fully integrated solution for smart home management. This project involved designing custom circuitry and creating professional-grade PCBs using CAD software, tailored to accommodate diverse room specifications for maximum flexibility and functionality.

I developed an integrated system comprising a web server, database, and a custom Android application, enabling independent management without reliance on third-party platforms. The system supports multi-platform control, allowing users to interact seamlessly via Google Assistant, Amazon Alexa, a dedicated website, and the custom Android app.

This project demonstrates my expertise in combining hardware and software to create an innovative, user-friendly IoT solution.
Tech Stack: HTML, PHP, MySQL, C++, ESP-32, HTTPS protocols, MIT App Inventor.

Research Paper: Demystifying Parallel Programming

I am currently authoring a research paper titled “Demystifying Parallel Programming,” which delves into analyzing parallel programming methods—namely OpenMP, OpenCL, and CUDA—to optimize computer vision tasks. This research evaluates the strengths and limitations of each method within the context of OpenCV applications, providing valuable insights into their real-world performance.

The study includes sample code snippets to illustrate implementations, alongside detailed performance metrics such as execution time and thread usage, to offer a comprehensive understanding of optimization strategies in parallel programming. The ultimate aim of this research is to contribute to advancements in parallel processing techniques for more efficient computer vision algorithms.

This project reflects my dedication to pushing the boundaries of computational efficiency and exploring the intersections of theory and practical application in high-performance computing.
Tech Stack: C++, CUDA, OpenCL, OpenCV, OpenMP, CUDA Toolkit, OpenCL SDK, Matplotlib, Seaborn.

Hotel Reservation System

The Hotel Reservation System is a robust and comprehensive hotel management solution designed to revolutionize how hotels manage reservations, employee tasks, amenities, and payments. Built with a modular, object-oriented approach, this project showcases my ability to design efficient systems that integrate multiple operational aspects into a seamless interface.

Key features include streamlined room and amenity reservation systems, secure payment processing, guest and employee management, and an intuitive manager dashboard. The system leverages abstract classes, interfaces, and reusable components to provide flexibility and scalability for various hotel sizes and needs.

This project demonstrates my expertise in designing and implementing complex software systems that integrate with real-world processes, creating practical and innovative solutions for the hospitality industry.

Tech Stack: Java, OOP Principles, UML Design, JUnit Testing, Git