PhD Dissertation Proposal Defense

This dissertation shows that two distinct fields - differential privacy and computational ecology - can be addressed through a unified methodological framework.

This dissertation presents a new foundation for flexible and secure replication of blackbox stateful services.

This dissertation addresses how computer science instructors can redesign course structures and pedagogy in response to the widespread availability of LLMs.

In the first part of my thesis, I introduce split parallelism, a novel  abstraction that addresses the limitations of traditional data parallelism on GPUs.

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

This dissertation proposes integrating transactional memory directly into a WebAssembly runtime system for persistent memory programming.

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

This thesis investigates the interplay between simulation and causal inference, focusing on how causal modeling can enhance simulation and vice versa.

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

This thesis addresses these limitations by developing a comprehensive framework for the automated assessment of open-ended mathematical responses. 

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

In this dissertation, I explore how lightweight dynamic analysis can be used to improve the reliability of Python software.