I am an visiting assistant professor of computer science at Carleton College. I teach both introductory and upper-level courses, with a special emphasis on the interface between CS and physical sciences. I taught intro to CS (CS111), Machine Learning (CS320), and created a new course called Computational Modeling and Simulation of Natural Systems (CS364). My background is in astronomy, physics, education, computation, and machine learning/AI. I like to work with others to find sustainable, data-driven solutions to complex and interesting problems. I am currently working on a new AWS platform that aggregates astronomical data.
My Ph.D. work was in astronomy and focused on modeling multi-wavelength observations of gamma-ray-emitting Classical Novae, specifically focusing on the V1324 Sco. I created a computational model for the thermal emission from the ejecta and fit the model using radio observations to probe the extensive properties of nova ejecta. I also used optical data as a plasma diagnostic, and gamma-ray data to constrain the dynamics of the event.
After my Ph.D., I moved into Physics Education Research at the University of Michigan. My work focused primarily on developing methods and tools to help physics instructors incorporate computation into their classrooms in an equitable and inclusive way.
I spent a year at Macalester College in St. Paul, Minnesota, where I had a tremendous time teaching in a small liberal arts setting for the first time. While there, I (co-)developed a Computational Physics course with Dr. Tonnis ter Veldhuis.
I then moved to Michigan State University, where I was an assistant professor (fixed term) working on Computation Education Research in the Computational Mathematics, Science and Engineering department. I studied how students solve computational data analysis problems, with the objective of making computation more accessible to folks from diverse backgrounds.
Dr. Tom Finzell 