Our Projects

Fall 2025

Supplier Portal

Supplier Portal

Developed a custom supplier portal designed to streamline how global companies interact with their vendors, creating a two-way bridge for managing risk, tracking procurement orders, and handling onboarding tasks

Amazon Project Leo

Amazon Project Leo

Built a full-stack application on AWS using ML to predict airport boundaries for compliance with satellite regulations, validated globally for accuracy and reliability

Vex

Vex

Developed an AI-assisted social platform enabling real-time, voice-enabled chatrooms where an intelligent agent participates in conversations, enhances discussions, and allows users to share and replay meaningful exchanges

Qubi

Qubi

Developed a full-stack mobile application that enables users to build, send, and visualize quantum circuits on different quantum computers while engaging with an interactive curriculum

MRI Visualizer

MRI Visualizer

Developed a web-based application that enables users to upload brain MRI scans, visualize them interactively, and run backend deep-learning models to generate and overlay tumor segmentation results in real time

Wildfire Prediction

Wildfire Prediction

Developed quantum-ML prototypes with IonQ for wildfire prediction and tensor-network neural nets by integrating quantum layers, fixing amplitude embedding, benchmarking on HPC, and compiling MNIST tensor networks into executable quantum circuits

AuditAssistant 2.0

AuditAssistant 2.0

Added AI-powered smart search for quick information retrieval and API-based web-native policy viewer to existing Medicaid policy analysis tool

Spring 2025

TrachSense

TrachSense

The team developed a compact CO2 sensing system that attaches to pediatric tracheostomy tubes, enabling continuous, remote monitoring to rapidly detect decannulation or obstruction and alert caregivers

Amazon Project Kuiper

Amazon Project Kuiper

Built a full-stack application on AWS using ML to predict representative clutter height for satellite ground station site selection, validated globally for accuracy and reliability

Malware Analysis and Visualization

Malware Analysis and Visualization

This semester's project involved developing a centralized malware analysis platform for various tools used by the company

Anomaly Detection & Visualization

Anomaly Detection & Visualization

Advanced U.S News' data platform by building a dynamic frontend for their internal API and implementing anomaly detection on multiple metric types

Citation Configuration

Citation Configuration

Created a web app to generate citations that supports uploading, filtering, and exporting policy data in an easy to use way

EmailMiner

EmailMiner

Developed a scalable Retrieval Augmented Generation (RAG) pipeline to better query information from emails, utilizing relationship mappings and similarity search databases to improve data retrieval speed and accuracy

Omal Learning Platform

Omal Learning Platform

Created a cross-platform application that transforms interaction with educators and clients, offering an all-in-one platform to learn, showcase skills, and find projects across diverse professions

CNH X-Ray Project

CNH X-Ray Project

The team trained a Graph Neural Network (GNN) on the ABIDE and sEEG brain imaging dataset to create an application that assists in Autism diagnosis

Mokhtarzada Project

Mokhtarzada Project

Developed a tool to automatically fetch relevant financial documents from websites using AI-based browser automation and construct a vector database of financial data to inform the user about market situations and provide detailed insights into specific industries

Warriors Legacy Project

Warriors Legacy Project

Developed an all-in-one mobile app for veterans, integrating healthcare access, AI-powered resume suggestions, video calling, and messaging to support medical, career, and community needs

Quantum Machine Learning

Quantum Machine Learning

Explored quantum machine learning for image classification, reproducing IonQ research papers, benchmarking against classical techniques, and testing quantum circuits on simulators before deploying to Aria-1 and Forte-1 ion-trap quantum computers