PhD Thesis Defense

Probabilistic models are essential for understanding complex systems across various fields, but inference in these models is often intractable.

This thesis addresses reconstruction tasks for static and dynamic structures, focusing on buildings and human faces exploring representations...

Our algorithms, Greedy Expert Round Robin and FairSequence, assign experts in such a way that no request "envies" another request's assigned experts.

In this PhD Thesis Defense, Chen will explore neural network architectures that facilitate joint learning across varied tasks.

In this proposal, Lee will present optimal online algorithms for energy optimization in the competitive analysis setting.

Kalanadhabhatta makes the case for an alternative sensing paradigm leveraging multimodal signals recorded during children's existing play-based interactions.

In this thesis, Bahramali explores 2 approaches to performing traffic analysis on encrypted network traffic: a model-based approach and a data-driven approach.

In their thesis, Cui leverages the pervasive ambient leakage signals, which are typically seen as detrimental, to enhance wireless communication performance.

This thesis puts forth a central focus on sustainability in electricity grids with the presence of distributed energy resources.

This dissertation explores the development and application of clinical foundation models (FMs).