Travis Canida is currently a second year MPH student in the biostatistics concentration within The Department of Biostatistics and Epidemiology. He attained his B.S in Mathematics with a specialty in Statistics from the University of Maryland, College Park. After spending a year working as an intern for the FDA's Center for Food Safety and Nutrition in the Biostatistics and Bioinformatics staff of the Office of Analytics and Outreach, he currently holds a full time position as a Mathematical Statistician within the aforementioned organization. He has worked on a variety of projects including the sodium reduction intiative, projects involving the analysis of metagenomic data, and has created an open source implementation of a Bayesian data mining algorithm using R.
Ottesen AR, Gorham S, Reed E, Newell MJ, Ramachandran P, Canida T, et al. (2016) Using a Control to Better Understand Phyllosphere Microbiota. PLoS One 11(9): e0163482. doi: 10.1371/journal.pone.0163482
Canida T., & Ihrie J. (2017) openEBGM: An R Implementation of the Gamma-Poisson Shrinker Data Mining Model. The R Journal 9(2), 499-519.