With the advancement of technology, we are able to collect, store, and transmit an ever-increasing volume of data. However, our ability to extract useful patterns from this massive amount of data is still lagging behind. Machine learning and signal processing…

ABSTRACT









Population size has been a matter of concern for rulers and states for centuries. Fears of over- and under-population led to extensive political debate and the implementation of numerous policies…

Early Americans defined themselves, and the nation, through their relations with the world. This dissertation explores a crucial aspect of these relations, examining how global commerce, and Americans' ideas about global commerce, produced theories and practices of power. It approaches…

Yes or no is perhaps the most common answer we provide each day. Indeed, binary answers to well structured questions are the building blocks of our knowledge. I started my research career in drafting such answers in various circumstances within…

The analysis of noisy consensus dynamics in networks is of great interest to both
advance the fundamental understanding of multi-agent systems in nature as well as
create robust decentralized engineering systems. We develop a protocol that heuristically attempts to optimize…

The United States is struggling to provide health care in the face of ever increasing demand. As medical students continue their decades long march toward specialization, questions of how to provide generalist care become quickly intertwined with that of who…

In this thesis we develop and test methods for numerically evolving hydrodynamics coupled to the Einstein field equations, and then apply them to several problems in gravitational physics and astrophysics. The hydrodynamics scheme utilizes high-resolution shock-capturing techniques with flux corrections…

Single-particle reconstruction of vitrified samples (cryogenic electron microscopy, or









cryo-EM) provides structural information for a large variety of biological molecules,









ranging from…

Machine learning is the science of discovering knowledge from data and making decisions based on this learnt structure. It has grown into a broad discipline that has established many statistical and computational learning principles. We are surrounded by the applications…

The goal of this project was two-fold: first, to improve the performance of machine learning
algorithms for the diagnosis of pediatric tuberculosis, and second, to use machine learning algorithms
to better understand the problem of diagnosis. We constructed and examined…