Ph.D. Presentations

Advanced driver-assistance systems (ADAS) are commonly organized as modular pipelines that transform raw sensor measurements into low-level actuation commands through perception, planning, and control. While learning-based methods have achieved state-of-the-art performance in perception and environment modeling, the planning layer remains a key bottleneck for reliable autonomy. Highway driving in particular requires long-horizon reasoning and socially […]

Modeling environmental extremes often involves large collections of spatial or temporal records where both clustering similar series and modeling dependence among extremes are challenging tasks. This Ph.D. proposal addresses several related problems in extreme value analysis. In particular, we study how to cluster many time series based on their extremal behavior using strategies defined via […]

Robotic space missions often use discrete event simulation to reduce risk in operation. A simulation applies a set of planned activities to a model of mission resources, and the model’s observed behavior is used to predict real-world outcomes. However, logically concurrent activities are typically simulated under one possible linearization of their events – an order […]

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 […]

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 […]