PhD Thesis Defense

This dissertation examines techniques for learning structure and discusses how the resulting background knowledge is used in decision making under uncertainty.

This dissertation explores how low-overhead dynamic analysis can be used to improve the reliability of Python software.

This dissertation develops a comprehensive framework for high-fidelity motion characterization, addressing challenges of sensitivity, robustness, and privacy.

This thesis addresses these challenges through a series of innovations in multi-task learning.

This research advances methodologies for analyzing textual content from large-scale online datasets, interpreting message intent, retrieving  knowledge...

This thesis proposes an alternative path toward intelligent control by  drawing inspiration from biological systems and exploring the concept of time-aware...

This proposal addresses three problems in fair ML.

This dissertation advances conversational AI by showing how multi-agent chatbots, thoughtful avatar design, and personalized interactions enhance engagement...

In this thesis, we revisit the task of data selection through the lens of social-oriented metrics like diversity and fairness.

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

This thesis addresses challenges of dataset scarcity and energy efficiency.

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