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…

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…

Academic-industry partnerships in biomedical research come in many forms, but
those that occur around clinical research are the most prominent. Researchers at academic
medical centers have historically conducted a large proportion of industry-sponsored
clinical trials, as they alone had the…

This thesis argues that Chinese firms can catch up with the technological frontier in the scope of new climate friendly energy technologies and provides a detailed study of the case of wind power.

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…

To investigate the influence of input from fellow group members in a constrained decision-making context, we develop four 2-armed bandit tasks in which subjects freely select one of two options (A or B) and are informed of the resulting reward…

This dissertation concerns itself with the effects of education and wealth on health in Africa. The first two chapters focus on the impact of adult education levels on the HIV epidemic in four sub-Saharan countries. The last chapter turns to…

The limitations common to linear imaging techniques were formalized succinctly by Ernst Abbe in 1873. In his theory, each Fourier component of a signal propagates independently from the source to the detector, and the corresponding feature can be detected only…

The central goal of compressed sensing is to capture attributes of a signal using very few measurements. The initial publications by Donoho and by Candes and Tao have been followed by applications to image compression, data streaming, medical signal processing,…