PhD Dissertation Proposal Defense

We focus on three fundamental processes: quantum teleportation with noisy memories, error correction in quantum storage, and distributed blind quantum computing

This thesis addresses challenges with robust algorithms tackling different aspects of uncertainty, including RL, resource allocation, explainability and LLMs.

This thesis advances fine-grained recognition under limited supervision  through several complementary approaches.

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

This thesis seeks to understand the extent of health inequity captured in EHR data and investigate how ML models can be redesigned to ensure they maintain...

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

This thesis contributes novel methods for differentially private statistical learning, with a focus on improving the usability of private inference...

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.