Dr. Neal Grantham
Dr. Neal Grantham is a data scientist and machine learning practitioner who specializes in the fields of spatial statistics, hierarchical Bayesian models, high-dimensional inference, and deep neural networks. He has extensive experience assembling reproducible data science pipelines with Python and R that transform raw, high-throughput sequencing data into informative visualizations and statistical analyses.
Neal’s research has primarily focused on the use of dust-associated microbial communities to geolocate objects with high precision across the United States and the globe. Related work has led to the development of a novel statistical model for the analysis of microbial abundance data from designed experiments. In his years as a research statistician, Neal has collaborated closely with microbial ecologists, horticulturists, marine biologists, EPA atmospheric scientists, and NASA aerospace engineers.
Neal received his Ph.D. in Statistics from North Carolina State University in 2017 and his B.S. in Mathematics, B.S. in Statistics from California Polytechnic State University, San Luis Obispo in 2012.