Education
- BA (with High Honors), Philosophy, UC Berkeley. Project: Heidegger and Searle on being-in-the-world
- MA, English, The University of Utah
- PhD, English, The University of Utah. Project: The Identity of Modernism
Biography
I have had a varied career. I studied philosophy as an undergraduate at UC Berkeley (BA, 1987), switched to literature for graduate school (PhD, 1999), and have held various faculty and administrative positions at the National University of Singapore and the University of Utah. From 2005 to 2014 I served as Associate Director of LEAP, a learning community for first year students at the University of Utah, and during that time began studying statistics, eventually doing research on student outcomes in LEAP using social network analysis, survival analysis and multilevel modeling. An internship in 2014 at Savvysherpa, a Minneapolis-based venture capital firm, turned into a job offer and a new career as a full-time quantitative researcher outside of academia. From 2015 to 2017 I managed the Office of Institutional Research and Reporting at Salt Lake Community College, directly supervising a team of analysts and statistical researchers. In 2016 I designed and started teaching a graduate-level course, Statistics and Predictive Analytics, in the MS program in Business Analytics (MSBA) at the University of Utah's David Eccles School of Business. I became a full-time Associate Professor (Lecturer) in 2018, continuing to teach Statistics and Predictive Analytics while also managing the MSBA Capstone program.
Other Profile Data
Tools: R, SQL.
Statistics: Linear and logistic multivariable regression, generalized linear models, multi- level/hierarchical modeling, Bayesian statistics, social network analysis, survival analysis, machine learning, time series analysis and forecasting, text mining, topic modeling, cluster analysis, simulation for model-checking and computing quantities of interest for statistical communication.
Research: Experimental and quasi-experimental research designs for causal inference, mixed methods, reproducible research.