CS5934: Capstone Project

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https://hdl.handle.net/10919/105656

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Now showing 1 - 20 of 123

PlusComm Bid Generating Web App
Rasnake, Joe; Roberts, Nathan; Ghayour, Saeid (2025-08-16)
The PlusComm Bidding Web App is telecommunications infrastructure bidding automation platform that transforms the traditional manual process of creating bid documents into an intelligent, data-driven workflow. The system combines a knowledge base of historical bid documents, AI generation, rule-based inclusion phrasing and document generation to automatically generate professional bid proposals by analyzing project specifications, finding similar historical projects, including necessary phrasing and applying to generalized templates that incorporate equipment lists, cost breakdowns, and technical specifications tailored to telecommunications infrastructure. The platform eliminates the time-intensive manual process of bid document creation through its sophisticated AI-powered generation engine that analyzes project requirements and automatically produces comprehensive Word documents with proper formatting, equipment tables, and cost calculations. Instead of spending hours manually researching similar projects, copying content from previous bids, and formatting documents, users simply input project details through a web interface and the system instantly generates professional bid proposals. The system was built using React.js for the frontend, FastAPI for the backend, PostgreSQL database for metadata storage, Google OAuth 2 for authentication and various AWS services for document storage and AI generation. The system builds intelligence over time by maintaining a knowledge base of uploaded historical bid documents, using document parsing and similarity scoring algorithms to ensure each new bid is informed by relevant past projects while maintaining consistency and professional quality across all generated documents. We have also uploaded this to YouTube: https://youtu.be/h6XRk2H1WM4
Eleos Access: Diaspora Concierge Hub
Zeno, Mary ; Vempuluru, Sruthi; Valaboju, Vrinda; Bangari, Neha (2025-08-16)
Eleos Access is a multilingual, web-based platform developed for Eleos Groups, designed to support members of the Ethiopian diaspora in the U.S. and Europe by enabling them to plan and pre-pay for essential services before arriving in Ethiopia. The application provides booking modules for travel planning, property management, and business support - each of which are reviewed and processed by Eleos Groups. A travel estimator powered by the Mistral AI model allows users to calculate projected travel costs, while integrated PayPal payment processing ensures secure online transactions for service requests. Users can register for personal accounts to submit their service requests and track payments, while administrators can oversee request payments and manage property listings. The system is built with a React.js frontend using Vite, Shadcn, and Tailwind CSS, and a backend powered by FastAPI and Uvicorn. Database management, user authentication, and email notifications are done through Supabase.
Electronic Health Records System for PIES Fitness Yoga Studio
Boldt, Devon; Noneman, Brett A.; Wiecking, Charles P.; Yeh, James C. (2025-08-15)
The PIES Electronic Health Record system is a full stack web application developed for PIES Fitness Yoga to support yoga therapists in securely managing client records, tracking session history, and completing therapy documentation. Built with a Spring Boot backend and a React frontend, the system provides role based access for junior and senior therapists, enabling intake form submission, SOAP notes, and self assessment workflows. Additional features include appointment scheduling, search and filtering of session records, document viewing and download, and integrated digital signature capture. The backend uses MySQL with Docker based deployment, JWT authentication, and Swagger API documentation, while the frontend is styled with Tailwind CSS and uses react-hook-form for dynamic data entry.
CS5934 Capstone Project: LeafRX
Hart, Sabrina; Park, Brian; Biju, Rayhan (2025-08-15)
RAG Chatbot For Creator Insights
Wakeley, Christopher; Hu, Deyu; Folomeev, Valery; Puppala, Sai (2025-08-15)
WagelboxPlusPlus
Agile development with client to improve their existing email marketing website by adding AI generation functionalities to email campaign creation to improve existing user experiences. This included, adding image recognition to have more relevant images recommended to a user, image generation to generate more relevant images, and email campaign generation to AI generate an entire email campaign for a more professional result. Project also included work on their website by modernizing, fixing bugs, improving existing features, and making it mobile responsive.
Financial Data Dashboard for Old Town Curated/Alps CFO
Hoang, Nhan; Wynn, Benjamin; Scott, Layla; Dugan, Parker (2025-08-12)
Melio Models
A symbiotic object-recognition site - where you and object recognition models learn together. Melio Models harnesses the natural human desire to learn, creating a symbiotic relationship between knowledge seekers and object recognition models. Like curious minds, these models improve with every new piece of input. By providing a platform where individuals and models share knowledge, both sides benefit. When a human’s knowledge falls short, the model can try to fill in the gaps in the Object Identifier. When the human wants to learn and test their skills, they can play the Learning Game. When the model needs improvement, the human can guide it through feedback. And when the model needs to expand the items it can recognize — or when an entirely new model is needed — that can be done in the Model Explorer.
Minecraft Final Presentation Demo - Group 10
Shah, Faraz Ulhaq ; Kumari, Sanjna; Assadi, Taeesh Azal (2025-05-04)
Career Compass: an AI career advisor
Karne, Anvita Sanjay; Chouthai, Atharva Bipin; Kumar, Drushya Chikkaballapur; Gutgesell, Julia Marie; Maddipati, Mahita; Belgundi, Rajat Ratnadeep; Deshmukh, Shubham Laxmikant; Kasera, Siddhi (2025-05-05)
Career Compass is an AI-driven career guidance platform that combines Retrieval-Augmented Generation (RAG), structured labor data from O*NET and BLS, and large language models (LLaMA 3.3) to deliver personalized, explainable career insights. The platform offers a real-time conversational chatbot and an embedded Career Insights Dashboard built in Tableau, enabling users to explore occupations, required skills, education, and job outlooks interactively. Designed for accessibility and scalability, it includes a semantic vector search engine, persistent conversational memory, and structured fallback logic to ensure accurate responses. The data visualization component translates complex employment and wage statistics into narrative-driven dashboards and interactive data stories, making labor trends more understandable for users without technical backgrounds. The application is deployed on AWS EC2 with a Next.js frontend and FastAPI backend.
U-Pass Manager
Kamath, Nidhi Govindraya; Mahato, Kunal; Nagar, Rajat; Kulkarni, Rashmi Dattatraya; Tirkey, Manim; Huang, Cheng-Chen (2025-05)
The U-Pass Manager is a cloud-based web application designed to automate and streamline the distribution of university transit passes, replacing outdated, manual Excel-based workflows with a scalable, secure, and real-time platform. Developed as part of a Capstone Project, at Virginia Tech, the system features robust role-based access controls for administrators and distributors, integrated NFC scanning for quick card assignment, AWS-powered backend services for data processing and communication, and a detailed analytics dashboard to support informed decision-making. By eliminating inefficiencies, the application enhances the accuracy, transparency, and scalability of public transit access for students, while enabling seamless coordination with external organizations such as WMATA.
PitDash: Live Surgery Dashboard
Lowry, Keith; Hoang, Brandon; Pradhan, Hansa; Kulkarni, Yash; Yeboah, Tesha; Panigrahi, Asmi; Bhavsar, Revati; Manavalan, Sudarshan (2025-05-09)
Homiez
Park, Esther; Rama, Shalini; Gowrishankar, Vasundhara; Somashekar, Shanmuganathan (2025-05)
Homiez is a web application that empowers property buyers and renters to stay updated on real-time price changes in the real estate market. Unlike traditional real estate platforms that prioritize advertisers, Homiez puts users first, offering a focused, distraction-free experience to track property price drops and increases. By simplifying how users monitor property trends, Homiez enables smarter, faster, and more informed buying and renting decisions.
GrantVault
Cui, Timothy (Tikki); Zimmerman, Ian; Naseh, Harris; Dhongade, Shardul (2025-05)
Roomly Application
Patel, Shalini; Shearon, Kelsey; Bansal, Ishi; Ganta, Kalyani; Anandarajan, Shareeya (2025-05-07)
Greek Right
Ulloa, Simon; Eichensehr, Vanessa (2025-05)
GreekRight is an application for fraternity and sorority management. Our application allows student leaders to manage their organization and allows members to access the information that they need. Our current solution has three major components: a calendar system to keep members informed of events, a shifts system to coordinate volunteers, and a messaging system for streamlined communication. We plan to continue to add features and allow each organization to choose and customize the features that best suit their needs.
EnQueue
Bone, Spencer; Goodman, Patrick; Yi, Branden; Ogura, Griffin; Kanjoor, Ajay (2025-05)
This project presents a web-based academic support platform integrated with Canvas via LTI and API, built using FastAPI and PostgreSQL. It provides a unified interface for managing student help queues, TA schedules, course rosters, assignments, and FAQs. With features like role-based access, TA location tracking, in-queue student games, and TA rating systems, the platform aims to streamline academic support in large university courses. By combining structured course data with real-time interactions, it improves responsiveness, reduces redundancy, and enhances the learning experience for students and teaching assistants alike.
CS5934 - NavagantAI
Dewey, Patrick; Gomez, Aaron; Jaimes, Alex; Kamalesh, Akhil (2025-05)
NavagantAI is a prospecting platform built for our client Navagant, a Richmond-based mergers and acquisitions advisory company. The core goal of this platform is to assist associates at Navagant in finding new clients through the use of historical outreach data and a machine learning model. NavagantAI was architected to ensure robustness, performance, and security, with a user-first design. The core feature of our application is company search, which finds companies based on various parameters (sector, keywords, number of employees, revenue, etc.) and ranks the results using a similarity score assigned by our model. Our search system is considerably faster than competing systems, retrieving results in just a few minutes—compared to the hours taken by similar commercially available systems. Users can view search results in tabular form from a web browser or download the results for use outside of the application. Searches and results are also saved, allowing users to revisit previous search queries and results. The speed and intuitive nature of NavagantAI position it as a powerful tool for prospecting, with the potential to redefine how Navagant finds new clients.
TutorTech: An Easier Way to Find Tutors and Tutees
Kolli, Atin; Elavarthi, Bhargava; Morris, Jerry; Nair, Krishna; Kersulis, Tomas (2025-05-07)
DriveSense
Brenningmeyer, Matthew; D'Alessandro, Kevin; Engel, Levi Robert; Borthwick, Gavin (2025-05)
Modern self-driving systems seek to remove control from the human driver, placing them in a monitoring role that humans do not perform well in. However, this same technology can be utilized to improve existing driver’s skills using a much cheaper piece of hardware already present in many vehicles, the dashcam. Our system uses a vision model and a set of heuristics to analyze this footage and provide driving statistics to the user, helping them to gain a holistic view of their driving patterns and trends. This information helps them to reflect and create actionable goals to improve their driving in the future. For instance, a driver that is consistently being passed by others when they are in the leftmost lane should consider moving over to enable the natural flow of traffic, a trend our system can identify.

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