Machine learning endows autonomous systems to uncover underlying structures and physical laws from measured data and to leverage these models for prediction and decision-making. As the costs of data acquisition, processing, and storage decline—and sensors become increasingly widespread alongside ever-improving algorithms—artificial intelligence has attracted significant attention in research and industry. Machine-learning methods are particularly attractive […]

Collaborative virtual reality environments have the potential to greatly impact scientific progress, especially those relating to existential human problems. Within these virtual environments, scientists could view and interact with spatial data in applications as part of their sensemaking process, however, there are design challenges and barriers to development. This advancement document presents research questions related […]

Program verification has been applied in many contexts (including videogames), but the scale and complexity of the examples that have been analyzed fall short of the ability to analyze many existing games without massive computational costs. My research focuses on automatic analysis and design of one particular game: Super Metroid, with the goal of creating […]

Reconstructing ocean dynamics from observational data is fundamentally limited by the sparse, irregular, and Lagrangian nature of spatial sampling, particularly in subsurface and remote regions. This sparsity poses significant challenges […]

Modern machine perception is powerful yet brittle: failing in response to subtle data adversaries and lacking mechanisms to learn from their errors. We address this challenge by progressing from diagnosing […]

This thesis investigates the use of deep learning for classifying wound infections from photographic images, using colony-forming unit (CFU) counts as a quantitative labeling standard. Leveraging the visual information in […]

Accurate assessment of wound healing progress is critical for optimizing patient care and preventing complications, yet clinicians currently lack precise tools to determine where a wound stands in the healing […]

The presence of coronary artery calcification is a strong predictor for future cardiovascular events where cardiac risk categories are quantified depending on calcification size. Dual-energy chest X-rays provide high contrast […]

WiFi-based indoor positioning is a widely researched area focused on determining the location of devices. Accurate indoor positioning has numerous applications, including asset tracking and indoor navigation. Despite advances, their […]