CS5934: Capstone Project

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  • Ripple
    Yu-Jung Chen, Justin Wu, Kai-Jo Ma, Saran Sankar (2023-12-05)
    Ripple is an innovative social media platform transforming how we discover and engage with video content. At its core, Ripple leverages the power of social connections to recommend videos, creating a unique 'Ripple effect' that amplifies content discovery through user networks.
  • MCCS Data Analytics Dashboard
    The Asset Protection business unit under MCCS needs dashboards so they can easily access relevant asset protection information from a single source of information. Currently, Asset Protection has to go to various sources within MCCS if they want shrink information or point of sale details. The goal of our MCCS Data Dashboard is to create a centralized location for all the needs of MCCS data analysts. The product offers multiple pages for both the point-of-sale transactions and consolidated shrink information, as well as customized health check pages with up-to-date metrics for each branch of MCCS that allow for easy access and close monitoring of the data. The data is displayed as a combination of tables, charts, and graphs along with filters and search functionality that allow for deeper insights on the data.
  • Torc Robotics: Rain Detection Solution "RainSense AI"
    Lowe, Alyssa; Holland, Darius; Weaver, Ethan; Andrade, Jason; Samuel, Jonathan; Cho, Minho (2023-12-06)
    Torc Robotics makes autonomous vehicles, specifically self-driving trucks. As such, they hope to make their vehicles perform as safely and efficiently as possible. This task becomes more difficult when the vehicles are subjected to adverse weather conditions, such as rain. The first step in making these vehicles perform better in rainy conditions is to give the vehicle the ability to determine whether it is currently “raining” or “not raining”. This information could then help in informing the vehicle to adjust its maneuvers based on the presence of rain. The machine learning solution we developed can make highly accurate predictions as to whether there is rain present in the vehicle’s localized environment. “RainSense AI” is an ensemble learning system that takes in data from various sensors already present on the vehicle. Namely, it incorporates image data from the vehicle’s front-facing camera and LiDAR point-cloud data from the vehicle’s two LiDAR sensors. This data is passed into our system, which consists of two main parts: a Convolutional Neural Network that processes the image data, and an Anomaly Detection algorithm that processes the LiDAR data. Each of the two processes can make individual predictions regarding the presence of rain. Our system uses both of these predictions to generate a final prediction as to whether there is currently “rain” or “no rain”. This system can run in real-time, taking in the most current data from the vehicle’s sensors and continuously generating predictions.
  • DiagnoSym: Disease Prediction System Using the Symptoms
    Naga Sekhar Reddy Kambham; Sindhuja Banka; Yuva Sri Vemulapalli; Akhil Palla; Yaswanth Chakiri; Meena Lohani (2023-12-06)
    The rapid advancement of artificial intelligence (AI) has led to a significant transformation in healthcare, particularly in diagnostic development and personalized treatment approaches. This project introduces DiagnoSym, a web-based system harnessing the capabilities of machine learning to predict potential diseases and assess their severity based on user-provided self-reported symptoms. Beyond traditional diagnostic functionalities, DiagnoSym goes a step further by offering users valuable health information, personalized preventive measures, and details of medical experts. The integration of machine learning ensures accurate predictions, while the platform's holistic approach aims to enhance efficiency, effectiveness, and user experience in healthcare delivery. As AI continues to evolve, DiagnoSym exemplifies the potential for technology to positively impact healthcare outcomes, empowering individuals to play an active role in their well-being.
  • GTA Management System
    Walters III, Albert; Diwan, Aditi; Fotedar, Ajinkya; Davis-Wallace, Liam; Botelho, Carson (2023-12)
    Our team has developed a full stack application to assist the Virginia Tech CS department in assigning GTAs to courses. Currently, GTAs are assigned manually using spreadsheets and scratch paper, wasting a lot of time and energy. With our solution, GTAs and courses are displayed in a web app, with drag and drop functionality incorporated to allow the user to move GTAs into and between courses. Additionally, our backend calculates some automatic placements based on student data the user can use as a starting point. Our system greatly simplifies the GTA placement process by making the placement easier and faster.
  • InclusiveHire - Unbiased Technical Interviewing Platform
    TJ Koonce, Parth Ranawat, Ayush Roy, Thomas Stapor, Riddhi Thanki, Srujan Vithalani (2023)
    We propose InclusiveHire, which is an unbiased technical interviewing platform. It is a system that maintains the basic functionality of other industry standard video calling tools like Zoom or Microsoft Teams with added functionalities to maintain candidate anonymity to the person giving the interview. We protect the candidates identity by modulating the voice to the interviewer as well as preventing the interviewer from seeing the candidate through their camera. The candidate is able to hear the interviewer in their normal speaking tone as well as share their screen to perform any technical activities required by the interview. Our goal with this system was to address hiring biases that may occur when the interviewer could potentially make a biased decision based on the physical appearance and sound of the candidate.
  • HokieX
    Chen, Guankai; Guo, Xiao; Wang, Muyang; Chen, Youwei; Chen, Kaiyi; Asher, Tim (2023-12)
    HokieX is an online thrift shop designed specifically for Virginia Tech students, faculty, and the surrounding community. It is novel compared to other similar platforms like Facebook Marketplace as it includes verification for VT affiliates, including students and faculty. With this feature, our application will have reduced numbers of scammers and scalpers compared to competitors. However, this feature does not exclude people who are not affiliated with VT: Blacksburg residents and others in the surrounding community can also sign up and use the application. Its local focus also lends itself to Blacksburg and VT as there is a strong sense of community in this area. This means that, although those with malicious intentions could still gain access to the system, the community will reject them using the report system and keep the platform safe organically.
  • illuminate - Where Mentors, Skills, and Success Converge - Capstone Project - Fall 2023
    Srivastava, Apoorva; Maheshwari, Ujjwal; Mehendale, Alok; Maddhuru, Mahesh; Gururaj, Abhijith (2023-12-08)
    Illuminate, the future of e-learning in software engineering. In today’s rapidly evolving tech world, software engineers often face challenges in skill development, mentorship, and practical application. That's where Illuminate steps in. Imagine a platform where you can access cutting-edge courses tailored to your career goals and receive one-on-one mentorship from industry experts. Illuminate offers a unique blend of personalized learning paths, collaborative project opportunities, and continuous professional guidance. Whether you're starting out or looking to advance in your career, our platform caters to every step of your journey, transforming how you learn, grow, and succeed in the tech industry. Join Illuminate and bring your career under the spotlight.
  • Rewordly - Paraphrasing Tool
    York, Evan; Teegalapally, Akshita; Chouhan, Dhruveel; Venkatreddygari, Hyndavi; Nayani, Sai Nikhita (2023-12-08)
    Rewordly is a product designed to improve the writing process and save writers time. The product is meant to be a user-friendly and efficient tool for paraphrasing content. The product consists of a user-friendly interface, where a user will submit the content that they wish to be paraphrased and view the results, as well as a machine learning model that will handle the paraphrasing process. The product is meant to serve the Virginia Tech community and to address the issues with similar paraphrasing tools currently on the market.
  • LetsGo: Your Online Travel Coordinator
    Juvekar, Shaunak; Malik, Abdul; Raghu, Ramnath; Sethi, Raghav; Upadhayaya, Shrikanth (2023-12)
    LetsGo: Your Online Travel Coordinator is a web application designed to address the challenges Virginia Tech students face when trying to coordinate group travel. Recognizing the difficulty in forming travel groups, particularly when individuals have diverse destination preferences, LetsGo serves as a centralized platform for VT students to connect and organize shared trips. Unlike existing solutions with limited scopes, LetsGo operates as a social network-like platform, enabling students to create profiles, specify their desired destinations, and connect with others who share similar interests. Through secure messaging features, users can communicate and plan their journeys collaboratively. One key feature ensuring user safety is the platform's verification process, allowing only verified Virginia Tech students to participate. LetsGo aims to enhance the travel experience for students by fostering a sense of community and making group travel more accessible, cost-effective, and enjoyable.
  • Hokie For U
    Akshay Reddy Narra; Charan Teja Chelle; Samhitha Pentaparthy; Siva Kumar Reddy Sangu; Siva Sagar Kolachina; Sushma Kumari Kakarla (Virginia Tech, 2023-12-08)
    HokieForU is an innovative platform designed for the Virginia Tech community, providing a space for Hokies to both seek employment opportunities and actively engage in community service. It goes beyond a typical job portal by fostering a spirit of collaboration and support among Hokies. Users can offer or find a wide range of services, from household tasks to tutoring, creating a network that benefits both job seekers and local communities. By connecting Hokies with local needs, HokieForU aims to empower individuals to make a positive impact on their neighborhoods while also facilitating employment opportunities within the community. It's a unique blend of job platform and community service hub, reflecting the diverse talents and generosity of the Virginia Tech community.
  • GenQ
    Alsheikh, Abdullah; DeVerteuil, Steven; Bernard, Cedric; Ganseh Soma, Pranav; Parameswaran, Aaditya; Vegesna, Saketh (2023-12-08)
    Our team, embarking on a semester-long project, leveraged available Learning Management System (LLM) resources to develop a tool designed to assist instructors in curbing cheating on online quiz platforms. This project uses OpenAI's public API to generate quiz questions based on topic meta-data uploaded by the instructor and administered by students.
  • HokieFit
    Sagar Atla; Mohith Kamanuru; Srikanth Karri; Sai Pavan Bathala; Aruj Nayak (2023-12-08)
    Hey, have you heard about HokieFit? It's this innovative platform we've created specifically for Virginia Tech students to revolutionize the way we share and engage with fashion. Picture this: you can post your outfits, tag them for different occasions, and get inspired by a diverse array of styles – all without revealing your identity. It's all about the outfits, not who's wearing them, thanks to our faceless posts policy and face detection tech. This means no bias, just pure fashion appreciation. Whether you're into vintage, casual, or professional looks, HokieFit is where your style finds its community. It's more than an app; it's a new wave in fashion, making it inclusive, judgment-free, and focused on creativity. Join us and be a part of this exciting fashion movement at Virginia Tech!
  • Writing Buddy - A Writing Evaluation Platform
    Gate, Malhar; Saxena, Rhea; Kumar, Vinayak (2023-05-08)
    Writing Buddy is a product designed and developed as a tool to help improve students improve their writing skills and also help graders such as teaching assistants/instructors to evaluate the written essays. The aim of the product is to assist students with grammar suggestions as they write for better articulation. The platform also provides feedback on essay structuring for effective communication through writing, as well as plagiarism checking for students as well as TAs/instructors. For checking, Writing Buddy analyzes written essays to check if they have been generated with the help of AI such as ChatGpt.
  • Monitoring Student Data Analytics Associated with Interacting in a Open EdX Course
    Ravi, Harish; Perez Lozano, Joan; Kim, Jong Heon; Rahimi bafrani, Raena (2023-05-01)
    The Boeing Company, an American multinational corporation that designs, manufactures, and sells airplanes, rotorcraft, rockets, satellites, telecommunications equipment, and missiles worldwide, has recently announced a technology research project called Asynchronous Learning Experience Ideas for Boeing. In this project, they are looking for a group of software engineers to develop code to monitor student data analytics associated with interacting in an OpenEdX course as a part of a technology research project called Asynchronous Learning Experience Ideas for Boeing. The analytics could have various degrees of utility for various stakeholders at Boeing. Technical Stakeholders might want to know about system metrics relevant to ensure operational excellence, ensuring infrastructure stability, real-time monitoring of system performance, etc. The non-technical stakeholders might be interested in knowing about the accessibility of systems, the utility of the courses towards a learning objective among other things. Thus we would like to design systems that allow a data scientist to derive insights of interest from the Open EdX ecosystem. The purpose of the system is to monitor and analyze student data analytics associated with interacting in an OpenEdX course. The system aims to collect and analyze data on student interactions with courses, quizzes, and videos, and generate visualizations and reports that can be used to derive insights into the learning effectiveness of the courses, as well as the system's performance and stability. The ultimate goal of the system is to demonstrate the capability of using OpenEdX as an alternative to CANVAS for a learning platform and to allow data scientists to derive insights of interest from the OpenEdX ecosystem. This observability system aims to provide valuable insights into the performance, reliability, and accessibility of the system, allowing for proactive identification and resolution of issues and improving overall system health and availability, as well as providing actionable insights into the utility of the courses towards a learning objective. The design goals of the system are including but not limited to gathering log data as the students interface with the Open Edx, providing real-time monitoring of student progress and performance and performing advanced data analytics. Ultimately, the design goals of the system is to provide comprehensive insights into student learning and engagement, while leveraging the existing capabilities of the Open edX platform.
  • Open edX Analytics
    Patel, Anand; Oladipo, Ebunoluwa; Anglister, Joel; Bhatnagar, Tapan (Virginia Tech, 2023-05-10)
    Open edX is an open source Learning Management System(LMS) that enables educators to create and deliver online courses. Boeing has requested an enhanced analytics and observability system to track various metrics related to student behavior so they can understand the learning behaviors of students and get monitoring data for the system. The challenge our our project is to design and implement a system that collects and processes data in a way that is clear and understandable so stakeholders can make informed decisions. The resulting system is a dashboard based on the various data points collected.
  • Semantic Vector Search using an HNSW Index for Twitter Data
    Raines, Nicholas; Samarth, Mehta; Lax, Kyada; Justin, Vita; Jonah, Bishop (2023-05-08)
    Semantic Vector Search is a promising alternative to keyword search for information retrieval systems. It allows for semantic meaning to be extracted from multiple different types of documents and doesn't rely on the underlying tokens of text-only documents in order to perform searches. One of the outstanding issues with vector search is that the K Nearest Neighbors (KNN) algorithm is O(N) time complexity, which does not scale well to enterprise applications. Hierarchical Navigable Small World (HNSW) retrieval systems attempt to solve this by implementing an Approximate Nearest Neighbors (ANN) in O(log(N)). This project implements both KNN and HNSW backends for an example use case with Twitter data. We found that the retrieval accuracy of the Vector Search systems was superior to a traditional keyword search system, and that the retrieval time of an HNSW backend not only greatly improves upon KNN, but is even comparable with keyword search.
  • Playpal
    Desai, Kirtan; Khosla, Tanvi; Gadhiya, Kahan (2023-05-08)
    A web app to find partners to play sports with in your city. People want to play sports but it’s difficult to find someone to play a team sport with, especially post covid when many people study as well as work remote. Users can select a venue based on the sport they want to play as well as look at people’s profiles and choose sport partners based on the ratings (on many criteria) on their profile they receive after they play a sport with another user.
  • Boeing Open edX Course Converter and Data Visualization
    Benish, Robert; Ross, Christian; Childs, Grayson; Chien, Hsin-Yu; Chen, Yi-Han (Virginia Tech, 2023-05-08)
    The goal of our project was to create an easy way to convert Canvas course content to the Open edX online educational platform and add more information about the course’s progress for the instructor. This goal was given to us by Boeing who wanted to analyze the capabilities of Open edX as a free open-sourced alternative to other online educational platforms. Our project seeks to fulfill the goal by creating additional functionality into an Open edX course. The added functionality includes a course converter that allows an exported Canvas course file to import into an Open edX course with the minimum effort needed from a user. The need for a course converter is due to the differing course structures and using a converter is much faster than adding content manually. A data visualization application was also added to give more insightful information to instructors about the course’s students. The data visualization application would provide graphs and charts for the students’ total session time on a course, general geographical location, assignment submission times and other useful information. This information is not available with a normal Open edX course. The functionalities were integrated into the Open edX course structure to allow for ease of use. Additionally, we were able to add these functionalities to a cloud-based course that could be accessed by anyone. The project followed an agile development process with frequent meetings and concise documentation.
  • Capstone Project: CourseQuest
    Feng, Yuechen; Lin, Yuching; Vannala, Raghavi; Lamba, Swati; Fang, Gary (2023-05-08)
    The objective of this web application is to build a safe and informative platform for students to engage and connect with each other to gather information and aid their decision in determining which courses to enroll in for their interested specializations. This platform will allow students to connect and network with other students, enabling them to form study groups, connect with alumni, job search, etc.