Data Science
Working with real datasets, finding patterns, and learning how statistical and computational tools turn data into insight.
I enjoy teaching computer science because it gives me the opportunity to explore ideas alongside students. Beyond understanding the theory, I want students to see how concepts work, ask questions, experiment, and create things of their own.
My teaching spans the foundations of computing, software development, and data-driven problem solving. These are some of the areas I regularly work with students on.
Working with real datasets, finding patterns, and learning how statistical and computational tools turn data into insight.
Understanding what happens beneath the applications we use—from processors and memory to processes, scheduling, and system resources.
Exploring how to approach problems, reason about efficient solutions, and translate those ideas into readable, reliable programs.
Looking at how information is organized and how software components coordinate, communicate, and work together.
One of my favorite parts of teaching is working with students as their projects move from an initial idea toward something that actually works. In senior capstone and independent research, the learning often comes through exploration: trying an approach, discovering what doesn't work, and figuring out what to change.
Those projects have led us into virtual reality, artificial intelligence, robotics, computer vision, and many other areas.
Explore some of the projects →I also enjoy making computing more approachable through hands-on data science and AI workshops, engineering summer camps, and outreach activities for students and educators in the Texas Panhandle. Teaching doesn't always happen in a traditional classroom.