I am a Research Statistician Developer at SAS where I am a part of a small team in Advanced Analytics R&D that designs and develops graphical user interfaces (“tasks”) in SAS® Studio to help make the analytical methods in SAS easier to learn and use.

SAS Studio is a more modern interface for SAS that you can use in place of the SAS Windowing Environment or Enterprise Guide®. SAS Studio is not a stand-alone product but is available with Base SAS® or SAS® Viya®. SAS Studio is also the primary interface that comes with SAS® University Edition, which is free to students, educators, and learners for non-commercial use, and can be installed on all three major operating systems. Yes, it actually works easily on Mac and Linux! If you use statistical software, I encourage you to check it out!

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.

Recent News

  • I will be presenting a paper and two software demos at SAS Global Forum 2019 in Dallas, Texas, which will be held April 28 - May 1. In addition to working the demo booth for SAS Studio tasks and SAS University Edition, I will be presenting at the following times:
Day Time Title Session Location
Monday 11:30 Learning Data Science with SAS® University Edition and JupyterLab 3133 D168
Monday 2:30 Build Fully Connected Neural Networks with SAS® Studio Tasks and SAS® Viya® SD409 Super Demo 4
Tuesday 3:30 Easily Perform Competing-Risks Survival Analysis with SAS® Studio Tasks SD321 Super Demo 3