I am a Machine Learning Developer at SAS where I design and develop graphical user interfaces (“nodes”) in SAS® Model Studio that empower you to perform data preparation and model building without the need to write any SAS code.

Model Studio is a comprehensive, collaborative visual modeling environment that enables you to easily train, analyze, and compare a variety of different machine learning models without writing any code. Model Studio is part of a collection of user-friendly visual tools that support the entire analytics life cycle—from data preparation, to exploratory data analysis, to model creation and deployment. These easy-to-use tools make data and analytics more accessible to a wider range of people, enabling them to use data to improve decision making.

Before joining SAS, I finished my PhD in statistics at North Carolina State University under the direction of Hua Zhou and Eric Chi. My research interests include machine learning, big and high-dimensional data, computational statistics, and statistics education. While in grad school, I served as an instructor for ST311 (introductory statistics) for several semesters. I also gained real-world experience as a Data Scientist Intern at MaxPoint Interactive and as a statistical consultant for the NC State University College of Veterinary Medicine. Please take a look around my website and feel free to contact me if you have any questions or comments.