Welcome!

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

SAS Global Forum 2019

  • I had a great time at SAS Global Forum again this year. I loved talking with users to hear how they use SAS, answer their questions, and see their excitement for my work that makes analytics more accessible for everyone.
  • I presented a paper and two software demos:
Type Title
Paper Learning Data Science with SAS® University Edition and JupyterLab
Super Demo Build Fully Connected Neural Networks with SAS® Studio Tasks and SAS® Viya®
Super Demo Easily Perform Competing-Risks Survival Analysis with SAS® Studio Tasks
  • You can explore and reproduce the examples in my paper by first installing SAS® University Edition (which is free for academic, non-commercial use) and then downloading the Jupyter notebooks and data from the SAS Global Form 2019 repository on GitHub. Your comments and questions are encouraged!
  • I plan to eventually create videos of my super demos, and I will post them once they are available (they are currently being edited, so stay tuned!).