PhD Dissertation Proposal Defense

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.

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

In this proposal our goal is to make generative retrieval scalable and practical for real-world information retrieval systems.

This thesis develops and analyzes algorithms for several key problems related to eigenvalue and eigenvector estimation...

This dissertation studies communication-efficient multi-device inference for Transformer models under bandwidth-limited settings.

In this thesis, we identify and rectify some remaining limitations of such cryptographic constructions and their proofs of security.

This thesis investigates architectural principles for large-scale quantum networks across three settings.

In the first part of this thesis, we formulate a general-purpose information-theoretic criterion that allows further improving SSL representations.

This thesis investigates generative models for parametric curves and surfaces.