PhD Dissertation Proposal Defense

This thesis presents a comprehensive investigation into the design, implementation, and analysis of resource allocation systems for modern datacenters.

This thesis presents multiple approaches for aligning LLMs with realistic student behavior.

This dissertation investigates how NLP methods can enable scalable educational assessment and AI systems across key components of the educational pipeline.

This dissertation studies the algorithmic construction of threshold-logic circuits for Boolean functions.

This thesis investigates how to design high-throughput, cost-efficient inference serving systems that adapt to time-varying workloads.

This thesis proposes a series of methodologies designed to overcome data scarcity.

This thesis addresses IMU data scarcity and energy constraints.

This thesis first establishes and empirically validates a causal model of the relationship between programming languages and energy consumption.

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

This thesis aims to advance both scalable, pedagogically-grounded AI systems and empirical understanding of how students currently use AI tools.

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

This proposal examines safe decision-making under causal uncertainty.