PhD Thesis Defense

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

This dissertation studies the fundamental limits of covert activity across communication, network attack, and sequential detection settings.

This thesis addresses challenges of dataset scarcity and energy efficiency.

This dissertation explores machine learning techniques for molecular property prediction, with a focus on modeling and understanding mycomembrane permeability.

The dissertation addresses the fundamental challenge of deploying machine learning models on resource-constrained autonomous systems

This thesis seeks to understand the extent of health inequity captured in EHR data and investigate how ML models can be redesigned.

This dissertation presents five systems that jointly optimize computation and communication across two workload regimes.

In this thesis, the author investigates the capabilities of LLMs to understand student behavior and provide appropriate feedback.

In this thesis, I address this problem by introducing multiple approaches for aligning LLMs with student behavior and knowledge.

This dissertation develops analytic pipelines and machine learning approaches to estimate ataxia severity.

This thesis contributes novel methods for differentially private statistical learning, with a focus on improving the usability of private inference.

This dissertation addresses emerging challenges, proposing innovative approaches to adapt A/B testing methodologies to modern constraints .