Join us as the School of STEM master\u2019s degree candidates present their culminating thesis and project work. The schedule is updated throughout the quarter, check back for new defenses.<\/p>\n\n\n\n
View previous quarter schedules<\/a><\/p>\n\n\n\n Select a master’s program to navigate to candidates:<\/strong><\/p>\n\n\n\n Computer Science & Software Engineering<\/strong><\/a><\/p>\n<\/div>\n\n\n\n Cybersecurity Engineering<\/strong><\/a><\/p>\n<\/div>\n\n\n\n Electrical & Computer Engineering<\/a><\/strong><\/p>\n<\/div>\n<\/div>\n\n\n\n Chair<\/strong>: Dr. Min Chen Blackfoot (Niits\u00ed\u02bcpowahsin) is a culturally and historically significant Indigenous language of the Blackfoot Confederacy and a primary medium through which community knowledge, identity, and oral traditions are sustained. As with many Indigenous languages, Blackfoot is experiencing ongoing endangerment, highlighting the need for accessible learning tools and culturally grounded resources that support intergenerational transmission and revitalization.<\/p>\n\n\n\n This paper presents the design and implementation of Blackfoot – Play and Learn, a web-based, game-driven language-learning application that integrates cultural context with structured, practice-oriented activities. The application is organized as a suite of modular learning experiences, including a Blackfoot History module and several interactive activities: Flashcards for incremental vocabulary acquisition, Blackfoot Builder for scaffolded construction of meaning through guided word selection, Voices of the Blackfoot for listening-centered engagement with narrative content and dialect identification, and a Quiz module for rapid recall and self-assessment. A persistent leaderboard provides lightweight gamification to encourage continued engagement and make progress visible across activities. Because Blackfoot is spoken across multiple dialects, the system incorporates dialect awareness throughout its modules rather than assuming a single standardized variety. The system is implemented as a React-based web application using client-side routing and reusable, modular UI components.<\/p>\n\n\n\n The project follows Agile development practices with iterative feature delivery and periodic review feedback. Emphasis was placed on code quality, modular design, reusable utilities, and backend best practices such as normalized answer checking, debounced availability validation, provider-aware reauthentication, and guarded asynchronous data access. The resulting system demonstrates a scalable, maintainable architecture for culturally informed, game-based language learning, and provides a foundation for future adaptive and community-driven extensions.<\/p>\n\n\n\n Chair<\/strong>: Dr. Clark Olson Indoor navigation has emerged as a growing challenge in large, complex buildings such as university campuses, hospitals, shopping malls, and corporate offices, where traditional signage is not always sufficient to provide consistent, accessible guidance. Outdoor Global Navigation Satellite Systems (GNSS) are unreliable indoors due to signal attenuation and lack of line-of-sight to satellites, while existing positioning systems such as QR-code markers and dedicated infrastructure introduce installation and maintenance overhead that scale poorly over time. These limitations motivate the development of scalable indoor positioning systems that leverage advances in computer vision, sensor fusion, and modern mobile computing. This project presents the design, implementation, and evaluation of an augmented reality-based (AR) indoor building navigation system that integrates 3D spatial modeling to enable scalable, user-friendly indoor guidance.<\/p>\n\n\n\n The system uses a server-backed architecture and a modular reconstruction pipeline to create building-scale 3D maps from phone-captured scans, organized into workspace-based reconstructions to support iterative refinement and long-term data management. For mapping, the pipeline uses learned features and robust pose estimation to produce a sparse 3D reconstruction. For navigation, the system performs real-time visual localization with rolling-window multi-frame matching against a pre-built 2D-3D descriptor database, estimating camera pose using Perspective-n-Point (PnP) with Random Sampling Consensus (RANSAC). A coordinate alignment transform maps reconstructed building coordinates into the user\u2019s live AR session coordinates, enabling stable AR labeling and route visualization. The overall design prioritizes minimal installation and maintenance compared to infrastructure-heavy alternatives such as fiducials and beacons, while supporting multi-floor buildings and scalable deployment.<\/p>\n\n\n\n The project is evaluated in UW Bothell\u2019s Innovation Hall, which involves scanning hallways, open spaces, and staircases. After the scanning process, all rooms, exits, elevators, restrooms, and scan connections are labeled using a label projection system that operates directly on the captured scan images. The scans are then merged into a unified building model, from which a navigation graph is generated and prepared for publication and consumer use. The resulting platform demonstrates the feasibility of scalable, infrastructure-light indoor navigation while highlighting practical challenges in visual positioning under descriptor ambiguity and perceptual aliasing.<\/p>\n\n\n\nMaster of Science in Computer Science & Software Engineering<\/h2>\n\n\n\n
WINTER 2026<\/h3>\n\n\n\n
Wednesday, February 25<\/h4>\n\n\n\n
DEBOSHRI DAS<\/h5>\n\n\n\n
Candidate<\/strong>: Master of Science in Computer Science & Software Engineering
11:00 A.M.; Join Deboshri Das’ Online Defense<\/a>
Project:<\/strong> Blackfoot – Play and Learn: Designing a Game-Based Language Learning Application<\/p>\n\n\n\nFriday, March 6<\/h4>\n\n\n\n
BENJAMIN V. SCHIPUNOV<\/h5>\n\n\n\n
Candidate<\/strong>: Master of Science in Computer Science & Software Engineering
1:15 P.M.; Join Benjamin V. Schipunov’s Online Defense<\/a>
Project:<\/strong> AROfficeNav: A Scalable Indoor Mapping and Augmented Reality Navigation System<\/p>\n\n\n\nWednesday, March 11<\/h4>\n\n\n\n
SAMMAN TYATA<\/h5>\n\n\n\n