The Right Livelihood International Conference is a five-week global conference exploring how education can strengthen democracy, collective intelligence, and just futures. Bringing together Right Livelihood Laureates, students, faculty, and community partners […]
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 […]