Ph.D. Presentations

Flow cytometry is a valuable technique in microbial research used to measure the optical properties of single-celled organisms at high throughput. Oceanographers often deploy flow cytometers on research cruises in order to study the characteristics of phytosynthetic microbes—called phytoplankton—in regions and times with diverse environmental conditions. Because cytometers cannot distinguish between subpopulations, researchers typically cluster […]

Oceanographic data, generated by modern technologies that measure biological systems across time, space, and cell populations, are often rich, high-dimensional, and highly heterogeneous. Such data provide valuable opportunities to study subcellular organization, cellular heterogeneity, and dynamic biological processes in marine environments. However, because marine plankton systems remain relatively understudied and less well characterized than many […]

Modern scientific studies increasingly rely on complex datasets exhibiting spatial and temporal dependence, particularly in social, environmental, and climate applications. This dissertation develops statistical models and computational methods for analyzing such data, with an emphasis on capturing dependence structures, nonlinear dynamics, and uncertainty quantification. A spatial deep learning framework is developed to extend classical geostatistical […]

Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However, in the modern era, computational environments have changed drastically, and we […]