Computational Mathematics
Leveraging statistical and mathematical models to quantify and control scientific uncertainty to further scientific discovery. Scientific research and development is a process of gaining fundamental understanding of physical, chemical, and biological principles through computational modeling, experimentation, and data evaluation. As a leader in applied statistics and mathematics research, we develop novel data-analysis methods to extract hidden features, anomalies, and signatures from high-dimensional, large-volume, multimedia data in support of discovery and confident decision-making. We develop methods and tools to optimize data-gathering approaches through sampling and experimental design.
Contact: Paul Whitney