tholscla at soe.ucsc.edu
She is currently working as a Postdoc at UC Irvine as a joint appointment in the Statistics and Computer Science departments under the advisement of Padhraic Smyth. Her research is focusing on applying statistical models to large data set for rainfall and microarray genetics.
She earned her PhD in Bayesian Statistics and Applied Mathematics under the advisement of Herbie Lee (UCSC) and Bruno Sanso (UCSC). The statistical research was based on modeling derivative curves with Gaussian processes. This method was applied to fitting the dark energy equation of state which is currently a problem on the forefront of cosmology.
She has also taught several mathematics courses, many sections, and statistical computer labs. She enjoys being around students and would like to continue to teach courses in the future.
She has further research interested in Bayesian models and inference. Some of her favorite courses were in modeling and inference. Some favorite special topics include: Bayesian non-parametrics, spatial models, correlated data structures and hierarchical modeling, DLM time series models, stochastic processes, experimental design, GLM, survival analysis, and regression and ANOVA problems. Her projects have included applications in cosmology, manufacturing, chemistry, and astronomy; she also has strong intrest in the biological sciences.