CS5934: Capstone Project
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- Career Compass: an AI career advisorAnvita Sanjay Karne; Atharva Bipin Chouthai; Drushya Chikkaballapur Kumar; Julia Marie Gutgesell; Mahita Maddipati; Rajat Ratnadeep Belgundi; Shubham Laxmikant Deshmukh; Siddhi Kasera (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 ManagerThe 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web application designed to automate and streamline the distribution of university transit passes, replacing outdated, manual Excel-based workflows with a scalable, secure, and real-time platform.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 DashboardKeith Lowry; Brandon Hoang; Hansa Pradhan; Yash Kulkarni; Tesha Yeboah; Asmi Panigrahi; Revati Bhavsar; Sudarshan Manavalan (2025-05-09)
- HomiezPark, Esther; Rama, Shalini; Gowrishankar, Vasundhara; Somashekar, Shanmuganathan (2025)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.
- Roomly ApplicationShalini Patel, Kelsey Shearon, Ishi Bansal, Kalyani Ganta, Shareeya Anandarajan (2025-05-07)
- Greek RightGreekRight 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.
- EnQueueSpencer Bone; Patrick Goodman; Branden Yi; Griffin Ogura; Ajay Kanjoor (2025)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 - NavagantAIDewey, 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 TuteesAtin Kolli; Bhargava Elavarthi; Jerry Morris; Krishna Nair; Tomas Kersulis (2025-05-07)
- DriveSenseModern 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.
- ChiralVizZachary Bibeau; Sparsh Joshi; Abhishek Satyanarayanan; James Wallace (2025-05-06)In this project, we create a molecular visualizer to aid students, faculty, and industry professionals alike in understanding the stereochemistry and properties of the compounds they work with.
- PerpThomas Rydzewski; Bradley Freedman (2025-05-04)Perp is a red/blue (purple) team operation simulator allowing your team to work against others to attack, defend, and maintain access to machines on a network. Access to machines is verified by submitting randomly generated flags to the centralized scoreboard which refresh every 10 minutes. The entire network is run off of a docker compose file, with each individual machine as separate dockerfiles, allowing extremely quick up or down scaling. It is easy to use, quick to set up, extremely cheap to operate, and more reliable than 6-7 figure commercial solutions.
- HomiezSomashekar, Shanmuganathan; Gowrishankar, Vasundhara; Rama, Shalini; Park, Esther (2025)
- Advanced Open-Source Intelligence (OSINT) Platform to Combat Misinformation on Social MediaKumar, Shekhar; Ummineni, Srikar; Lyu, Ran; Mondal, Sourav; Muthe, Laxman (2024-12)The AI-powered Open-Source Intelligence (OSINT) platform addresses the critical issue of misinformation on social media platforms, such as Twitter, by leveraging advanced Machine Learning (ML) and Natural Language Processing (NLP) techniques. This platform enables real-time analysis of textual data to detect and combat fake news, hate speech, and manipulated media. Its primary goal is to contribute to a safer and more reliable social media ecosystem by providing tools to identify misinformation, analyze its societal impact, and mitigate its spread effectively.
- CourtMetrics: Unlocking Tennis Insights with Machine LearningGali, Gautham; Pochamreddy, Ashutosh Reddy; Sardar, Atharva Rajendra; Satpute, Lokesh Devendra (2024-12)CourtMetrics is an advanced tennis analytics platform designed to enhance player performance and game analysis. It leverages cutting-edge machine learning models and Azure OpenAI services to deliver detailed player insights, match statistics, and video analytics. The platform enables users to upload or analyze match videos, compare player statistics, and visualize game trends through an intuitive dashboard. From coaches to analysts, CourtMetrics aims to revolutionize how tennis performance is evaluated by combining AI, data visualization, and user-friendly features.
- D.C. Crime Insights ApplicationWu, Ka Wai; Sung, Pei-Hsuan; Lin, Kuan-Fu; Marrero, Alexander; Kanakamedala, Venkata Chaitanya (2024-12-11)The D.C. Crime Insights application is an advanced web-based platform designed to analyze, visualize, and predict crime data in the D.C. area. Its goal is to offer users intuitive, data-driven tools, including an AI-powered chatbot, crime prediction analytics, safe routing, crime mapping, comprehensive graphs, and a report generation feature. The application uses data from an Amazon RDS database, updated daily using an auto-scheduler powered by AWS EventBridge and AWS Lambda. By combining advanced analytics with interactive visualizations, the platform allows users to explore a variety of crime metrics and gain valuable insights into crime patterns and trends.
- BiteRight VideoHuber, Samuel (2024-12-09)
- Civil War Photo Sleuth ChatbotAiken, Britney; Dixit, Kuldeep; Nongni, Thaddeus; Ramachandran, Kirubanidhi; Sarkar, Shivangi; Swecker, John (2024-12-11)The primary task of this project is to develop a conversational, interactive chatbot that is able to assist users of the Civil War Photo Sleuth website. Historians and researchers face difficulties accessing and analyzing fragmented Civil War archives, slowing the research process. Tools like Civil War Photo Sleuth (CWPS) offer valuable resources, and this chatbot seeks to improve the efficiency of this research collection.