2017 Winner of the Systers Pass-It-On Award
Project: Bayesian Networks
Melissa is from Greenville, SC, and wanted to find a way to promote women’s safety. Women are overwhelmingly more likely to be murdered, sexually assaulted, and stalked by men in the United States. In England and Wales, in the years 2015 to 2016, violent crime against women and girls reached a record high. These cases can be difficult to prosecute due to witnesses fear of retribution, as well as due to the variabilities of trace evidence that are often used to prosecute these crimes, such as hairs found without DNA.
The proposed project will use the principle of Bayesian Networks to analyze, quantify, and better provide statistical probabilities. Bayesian Networks are a statistical tool for which computer analysis is needed to effectively compute the resulting statistical probabilities. They are models which describe how variables are related via statistical probabilities, and work as a method of viable statistical analysis for use in trace evidence.
“Both as a student and as a graduate teaching assistant, I worked extensively programming Statistical Analysis Software (SAS) to run both basic and complex statistical modeling applications to obtain experimental results,” Melissa said. “Since completing my MS, I have worked as a scientist, a senior research technologist, and, most currently, with the US federal Social Security administration disability program. I have utilized my computer knowledge at each of these jobs.”