Associate Professor, School of Computer Science
My research interests center on developing and using machine learning and data mining methods for real-world applications with a special interest in high-impact weather and in space. Much of my current research focuses on developing spatiotemporal relational data mining methods and applying these methods to multiple real-world applications. I have applied the techniques that my students and I have developed to tornadoes, hail, severe wind events, flooding, drought, and aircraft turbulence.
To create a top science, technology, engineering, and mathmatics (STEM) workforce, we need a diverse and flexible workforce. Diversity will bring new ideas to the forefront and flexibility is required when technology is changing so rapdily. I'm interested in developing and applying innovations in STEM education that enable us to better train the scientists and engineers of tomorrow. I'm also interested in ways to significantly improve the diversity of our STEM workforce and I actively work on outreach projects to recruit a more diverse workforce. I have also developed a fully online class focusing on CS principles, which can recruit new STEM majors and train teachers for CS.
I direct the Interaction, Discovery, Exploration and Adaptation (IDEA) lab. You can find more information on our research from the lab web page.
[Publications] [Courses] [I run a blog for scouting resources (focused on Boy Scouts of America)]