This dissertation studies the integration of analytical modeling and optimization, machine learning, and Bayesian learning to optimize cost, access, and quality of healthcare delivery. Chapter 1 models computer-aided triage (patient prioritization) as feature-based priority queuing where types (diseases) are not perfectly observed but are inferred from observed features using a...
Protein-based biomaterials are widely used in biomedical applications and mechanical support because of their novel structural flexibility, biocompatibility and mechanical properties. Protein-based biomaterials outperform traditional synthetic materials in various environments as traditional materials lack the diverse chemical functionalities that proteins offer. Novel bioinspired techniques such as directed evolution offer the...
While there is high demand for university computer science (CS) courses, students often struggle when learning to program. Prior work has identified that student perceptions of their programming ability may contribute to these challenges. For example, studies show that students often perceive that they do not belong, are not capable...
This multi-study dissertation explored technology and creativity within three different technology-rich creative musical spaces. Through the use of three contrasting empirical methods (qualitative content analysis, intrinsic case study, and phenomenology), I explored the complex ways technology and musical creativity are linked. In the first study, I completed a content analysis...