PhD Dissertation Proposal Defense

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

In our work, we show that common data-splitting mechanisms thought to be a good proxy for out-of-distribution performance have significant cross-split overlap.

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

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 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.

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

In this thesis, I address this challenge across several computer vision problems by developing methods that adapt standard models to the open world.