PhD Dissertation Proposal Defense

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

In my dissertation, I propose to explore the vast landscape of quantum networks by devising analytical models for network performance.

This dissertation aims to utilize LLMs to mine, explain, and characterize global media coverage.

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

In this thesis, we first focus on discrimination in supervised learning.

This thesis addresses both specification and scalability challenges in agentic system alignment.

Cloud computing and rapid data growth have driven many organizations to outsource large datasets to cloud databases in order to reduce management costs.

This thesis proposes resource management techniques that mitigate performance degradation caused by such real-world dynamics to ensure robust performance. 

In this thesis, we show that changing current adoption trends could increase CO2 reduction by 40%, using multi-objective evolutionary learning.

This thesis explores the design of a multimodal teacher dashboard that is not tied to a single activity or embodiment type.

In this thesis, we explore how recent progress in generative modeling improves solutions to inverse problems.

This thesis develops and analyzes principled, efficient, and scalable algorithms for answering marginal queries under differential privacy.