Major in Computer and Information Systems Engineering.

Cumulative GPA: 3.6 / 4.0

Relevant Coursework: Data Structures and Algorithms, Software Engineering, Artificial Intelligence, Machine Learning

F1GPT is a domain-focused AI assistant built with Next.js and powered by GPT-5 through the AI/ML API. It uses a Retrieval-Augmented Generation (RAG) pipeline that scrapes and indexes authoritative Formula One sources — such as Wikipedia and the official F1 site — into a vector database (DataStax Astra DB). When a user asks a question, the system embeds the query, retrieves the most relevant chunks, and streams a GPT-5 answer enriched with this context. The chatbot is deployed with a sleek Formula One-themed UI, enabling real-time streaming responses. Its technical stack includes Next.js 15, Vercel AI SDK, LangChain text splitters, Puppeteer for scraping, and Astra DB for high-performance similarity search. Value & Use Cases: - Fans can quickly look up race results, driver stats, or rule explanations. - Journalists can explore historical data and technical regulations faster. - Teams & Analysts can leverage a conversational layer over structured F1 data. By combining GPT-5’s reasoning power with RAG, F1GPT reduces hallucinations and delivers trusted, up-to-date answers. This positions it as a unique sports-focused AI assistant, showing how AI can enhance fan engagement and knowledge accessibility in high-data domains like Formula One.

The Final Year Design Project aims to improve object grasping and manipulation in warehouses. It features an autonomous robotic arm that efficiently retrieves items from any defined place using dual monocular cameras for 6D object pose estimation and techniques involving robotics and machine learning for grasping strategies that includes kinematic modeling and inverse kinematic modeling of the robotic arm.

Developed a chat application using Nextjs and DotNet for a client who wanted a fast and scalable solution for online communication. The chat application allows users to register with their email and password, create a profile with their name and avatar, and chat with their friends in real-time. The chat application also supports file sharing, emoji, typing indicators, and message history. The front end was developed with Nextjs, a React framework that enables server-side rendering and static site generation. The backend was developed with DotNet, a cross-platform framework that provides a rich of libraries and tools for building web applications. The chat application uses Pusher, a cloud service that handles the WebSocket connections and the real-time messaging functionality. The chat application is hosted on Vercel, a platform that optimizes the deployment and performance of NextJs applications.

Engineered an advanced Restaurant Management Application using Reactjs for a lively frontend and Node.js for a robust backend. The app features intuitive order handling, efficient table reservation, and comprehensive inventory management, highlighting proficiency in developing streamlined, user-centric systems for the restaurant sector.

Constructed a comprehensive Inventory Management System as a web application, utilizing Django Python for

backend operations and MySQL for effective data storage. The system features intuitive interfaces and optimized

inventory monitoring, exemplifying expertise in full-stack development with an emphasis on dependability and

data handling.