PhD Dissertation Proposal Defense

This thesis presents a comprehensive framework for developing an autonomous quadruped guide dog robot while aligning with the practical needs of BLV users.

This proposal provides a unified framework for developing more accurate, scalable, and privacy-aware personalized LLMs.

This dissertation evaluates curriculum aware adaptive tutoring systems and computational learning platforms.

This thesis develops and analyzes compact formulations for decision-making problems characterized by large action and large state sets.

This thesis develops datasets, methods and theory to support the peer review process in both the pre- and post-LLM paradigms. 

This thesis reframes low dimensional representation as a coordinate-learning problem.

This dissertation addresses this limitation by developing AI and clinical natural language processing (NLP) methods that transform longitudinal narrative data.

This dissertation develops methods for accurately measuring user trust in software and creates automated techniques for making software more trustworthy.

In this proposal, we investigate properties in two challenging dynamic applications: consistent $k$-center clustering and light spanners in doubling metrics.

This thesis explores the design and implementation of ultrasonic sensing systems allowing devices to perceive and interpret signals beyond the audible spectrum.

The central research question is how geometric constraints and imperfect priors can advance spatial understanding.

This thesis explores new spatial shifting techniques to reduce carbon emissions while maintaining performance.