I am a data scientist. My research teams use the sensibilities of scientists to explore and draw inferences about the world from large data sets of many kinds.

We have a long heritage of work in astrophysics. For the last 20 years, we have used survey data to publish papers on many topics: ultra-high energy cosmic rays, variable stars of many kinds, galaxy masses and morphologies, galaxy filaments, groups, and clusters, quasars, meteors, gravitational lensing, gamma-ray bursts, x-ray astronomy, and cosmology. Our main data sources have been the Sloan Digital Sky Survey, the Robotic Optical Transient Search Experiment, and the Dark Energy Survey.

In recent years we have branched out, turning most of our attention to Learning Analytics: using data to understand and improve teaching and learning. We are exploring grading patterns and performance disparities both at Michigan and across the CIC, developing a variety of data driven student support tools like E2Coach through the Digital Innovation Greenhouse, an innovation space for exploring the personalization of education, and launching the NSF funded REBUILD project. REBUILD is an interdisciplinary collaboration, fostering the creation of intergenerational research teams including undergrads, grad students, postdocs, and faculty who will apply a scientific, evidence-based approach to teaching and learning in physics, chemistry, astronomy, biology and math.