PhD Dissertation Proposal Defense

This dissertation focuses on advancing wearable technology-based models for assessing physical and behavioral phenotypes.

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

This dissertation addresses key aspects of TCAP by proposing novel methodologies that enhance value estimation...

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

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

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

This thesis will use topological information captured by bonds to compare crystal networks.