- Ph.D., Statistics, University of California, Los Angeles (UCLA), 2022
- M.A., Applied Statistics, University of California, Santa Barbara, 2011
- B.S., Statistics, California Polytechnic State University, San Luis Obispo, 2010
- SAS Certified Base Programmer for SAS 9 (2008)
- Graduate Student Researcher, Department of Statistics, UCLA, 2018-2020
- Teaching Assistant, Department of Statistics, UCLA, 2018-2022
Dr. Andrew Kaplan is a statistical Scientist in Exponent's Data Sciences practice with 10+ years of experience analyzing large and complex datasets. He is an expert at analyzing both epidemiologic and clinical trial data. Dr. Kaplan is also skilled in multiple statistical programming languages including R, STATA, and SAS.
Dr. Kaplan's breadth of training and experience enable him to provide invaluable statistical guidance and expertise to a wide variety of Exponent's projects, including those in utility, automotive, and healthcare industries. His interdisciplinary project experience requires that he is constantly finding new ways to apply quantitative analysis to emerging and evolving problems.
Dr. Kaplan received his Ph.D. in Statistics from UCLA in December 2022, where his research work employed point process models to a variety of epidemiologic applications such as forecasting the prevalence of various communicable diseases and predicting doubling time during notable surges. He developed a non-parametric version of the recursive point process model, an adaptation of the known Hawkes construct that allowed for variable rates of disease spread due to population immunity. His model was proven to outperform other comparison models for fitting and forecasting cases of mumps in Pennsylvania. During the COVID-19 pandemic, he analyzed doubling trends and accurately predicted case counts of SARS-COV-2 both in California and nationwide.
Dr. Kaplan previously worked for five years as a statistician and data manager for the UCLA Department of Radiology. His responsibilities included consulting on several feature selection and data science projects within the department and medical center. He was also a data analyst on many clinical trials, including a phase III study for a drug that proved to be highly effective in treating patients with renal cell carcinoma.