Images, matrices, functions, trajectories, trees, or graphs are examples of objects increasingly encountered in modern data analysis. Statistical analysis of such object data requires skills and knowledge that are not (yet) part of a standard training of a statistician. This includes modern data handling skills, such as accessing web services, or manipulating large data in complex formats; skills needed for working in a multi-disciplinary scientific environment; and also mathematical skills, in particular involving notions of geometry, shape or topology. The project provides training to undergraduate and graduate students, addressing these issues through data analysis applied to important scientific questions, exposure to research in advanced methodologies, corresponding relevant mathematical theories, and computing. Graduate students and postdoctoral fellows also receive training in teaching, mentoring, scientific writing and communication skills, and also in other aspects that are essential for a successful academic career, such as grant writing and job application.
Continuous technological advances go hand in hand with a rapid increase of novel, complex data types, and the importance of developing skills necessary for their analysis cannot be overstated. Aspects of geometry and computing often lie in the center of such an analysis. The project is thus critically advancing training related to the analysis of such modern data types, thereby striving to provide a model for a broad, modern training in statistics. The project builds on the experiences and the strengths of the senior personnel, the affiliated members and collaborators from scientific fields including applied mathematics, astronomy, bio-demography, computer science, and neuroscience. The training activities will not only further strengthen the statistics program at UC Davis, but will also make critical contributions to enhancing the workforce in the STEM disciplines.