Shop the Frame is a Chrome extension + Express backend that lets you capture a YouTube video frame, detect items in the scene with Gemini, and return Shopify product matches.

Built a Python deployment automation tool integrating Vercel CI and IBM Cloud Code Engine, reducing deployment time by 20% for developers by eliminating repetitive ibmcloud CLI configuration.

Shipped a production React application using Shopify SDKs and live product APIs to integrate commerce data into gameplay. Selected from 150+ participants; deployed and maintained on the Shopify Shop app.

Developed a custom UDP file transfer protocol with stop-and-wait ARQ and error simulation; collected and visualized 8+ performance metrics including throughput vs. error rate using data plots and comparative analysis.

Developed and deployed a golf training tool, ForeSights, leveraging YOLOv5 for golf club detection with 98.0% accuracy and an Intel RealSense Depth Camera for 3D tracking; fine-tuned a large language model (LLM) using Cohere to provide real-time golf swing feedback. Led backend deployment using Google Cloud Platform and ngrok to host the web app, incorporating WebSockets for real-time data updates and enabling seamless integration of computer vision, machine learning, and user interface features.

Deployed an ATS resume scanning tool hosted on Vercel and the backend managed in a Docker container on Google Cloud. Utilized NLP techniques by leveraging the SpaCy en_core_web_sm pipeline to break down and tokenize text, extracting and comparing keywords against industry standards.

Developed a real-time detection system for impaired driving using YOLOv8 and live video feed classification. Created React dashboard to stream 6+ camera feeds for law enforcement; recognized by the Mayor of Kingston. Winning submission at QHacks '24.

Designed an AI-powered mobile stylist using LangChain and SQL to generate outfits from a user's closet. Achieved 95% recommendation accuracy; implemented natural language prompts for real-time feedback. Designed Dilliad, a fashion app offering personalized outfit suggestions, leading to a waitlist of 40 users and receiving first place at QTMA x McKinsey Pitch Day 2024.

Led development of a Chrome extension for "Scholar Pups," integrating Retrieval-Augmented Generation (RAG) using Llama 3.1 and LangChain to provide personalized scholarship application support; designed to simulate the guidance typically accessible to more privileged students by analyzing user inputs and matching them with relevant scholarships and AI-generated writing suggestions based on real application criteria.

Collected, cleaned, and classified walking-running data to create an AI classifier using a regression model using SciKit-Learn. Designed a graphical user interface using TKinter to allow users to analyze their data.

Created a light switch attachment that used an Arduino MKR to mechanically turn off and on a light switch using Alexa voice commands. Pivoted from a React app to Arduino programming, utilizing API calls within the Arduino IoT Cloud service, and integrated Alexa functionality through cloud integration. Created a contest website allowing users to input contest details, with real-time updates to a connected noSQL database.