In the professional setting, I have experience in data entry, IT, software engineering, customer service, management, and my education has given me intermediate Java and JavaScript programming skills, R programming, SAS programming, project management knowledge, and mathematics including but not limited to regression, statistical theory, machine learning, pattern recognition, and statistical computing.

My senior thesis research project, for my BS in Computer Science, used historical data to forecast the stock market with Artificial Neural Networks by forecasting future closes. I continued my machine learning research, completing a Kaggle project, by data mining short answer essays and using various techniques to automatically grade them. My current research is focused on Bayesian, nonparametric frameworks applied to multiple testing, density estimation, GLMMs, Meta analysis and supervised learning; copies of many of these projects are available through the resources tab.

Please download a copy of my CV, teaching dossier, and research dossier. Also, for those interested, here is my teaching dossier from University of South Carolina, pre-academia resume and here are my Myers-Briggs and Team Dimensions personality profiles.

Please feel free to contact me with statistical consulting and/or collaboration opportunities.