Visualization and Uncertainty Quantification for Vector Fields, Biomedical Engineering, and Chemical Education
In this talk, I will summarize some of my previous and current activities in uncertainty quantification and scientific data visualization. First, I will talk about the visualization of multi-modal ensemble vector fields. Key to this work are useful methods for interpolation of non-parametric probability density estimates. I will demonstrate the usefulness of interactive visualization in the Neurostimulation Uncertainty Viewer (nuView or νView) tool. νView provides a collection of visual methods to explore activated tissue to enhance understanding of electrode usage for improved therapy with Deep Brain Stimulation (DBS). Lastly, I will describe future research in the area of visualization and training software for student assimilation of concepts related to X-ray diffraction studies. This research will utilize models deposited in the Protein Data Bank (PDB).
Dr. Hollister earned his Ph.D. in Computer Science from the University of California at Santa Cruz in 2015. He then worked with Chris Johnson at the Scientific Computing and Imaging (SCI) Institute as a postdoctoral fellow. Currently, he teaches courses in computer graphics, data visualization, and introductory computer science at the California Polytechnic State University.