Upcoming Doctoral Dissertations

"Artificial Intelligence (AI) has rapidly transformed scientific research, industry, and everyday life. The rapid evolution of AI models, particularly large language models (LLMs), has dramatically increased the computational and memory demands of modern AI workloads. As AI models continue to grow in scale and complexity, performance bottlenecks increasingly arise across multiple layers of the AI systems stack" Read more

"Artificial intelligence (AI) has growing potential to support clinical decision-making by detecting health risks, interpreting predictive patterns, and enabling timely personalized interventions. However, many clinical AI systems remain limited by black-box predictions, static explanations, and limited adaptation to users' emotional and cognitive states. These limitations are especially critical in behavioral health, where risk states fluctuate in daily life and effective support requires transparent, emotionally appropriate, and shared understanding between patients and clinicians. " Read more

"Ocean waves carry an abundant renewable resource, but the most energetic waves occur in deep water, where wave energy converters can no longer be hinged to the seabed and must instead be mounted on moored floating platforms. This dissertation examines two moored converters tested in the Davidson Laboratory wave tank" Read more

"Electron transport in semiconductors can be significantly influenced by external magnetic fields, giving rise
to magnetotransport phenomena such as the quantum Hall effect, spin–orbit coupling, and magnetoresistance.
These effects have attracted considerable interest due to their potential applications in next-generation
optoelectronic and spintronic devices. Among semiconducting systems, two-dimensional (2D) materials are
particularly promising because of their tunable electronic and magnetic properties, strong spin-orbit coupling,
and diverse crystal symmetries." Read more

"Traditional graph theory has been widely adopted to address a broad range of graph-structured data problems. Recent advances in artificial intelligence have successfully integrated neural network techniques into network analysis. In particular, Graph Neural Networks (GNNs) have demonstrated remarkable effectiveness in learning node representations and identifying clustering patterns in graph-structured data." Read more

"In the acute respiratory distress syndrome (ARDS), a form of acute lung injury, inflammation increases the permeability of pulmonary capillaries. As a result, proteinaceous liquid leaks from the capillaries into the smallest pulmonary airspaces, the alveoli. The condition is known as alveolar edema. Additionally, surface tension at the interface of a thin liquid layer that lines the alveoli is elevated. Edema and elevated surface tension impair oxygenation." Read more