About Me
I am a PhD candidate in Statistics at Baylor University with a passion for understanding and learning from data to help others make informed decisions. I especially love collaborating with people with different backgrounds and learning about other fields so that I can better understand and approach problems.
As an undergraduate, I worked for a year as a research assistant developing Bayesian models to estimate elemental profiles and contributions of various potential pollution sources across the intermountain west. This project resulted in my first co-authored publication.
While at Baylor, I have had the opportunity to work on a variety of different projects that have helped me develop my skills as a statistician and data scientist. As part of my duties as a graduate assistant at Baylor, I:
- assisted in the development of a multi-day data science workshop for professionals in the water/wastewater treatment industry.
- worked as a statistical consultant studying and applying various statistical methods to help clients understand their data on a case-by-case basis.
Currently, I am working with my advisor, Dr. Mandy Hering, to improve multivariate statistical methods for detecting faults (anomalies) in complex processes, with specific applications in water/wastewater treatment.
Through my coursework and research, I have gained experience with a wide variety of methods and technologies, including:
- popular machine learning methods (KNN, random forests, XGBoost, neural networks, etc.)
- statistical methods (e.g., Bayesian methods, generalized linear models, time series)
- R (tidyverse, R Shiny, etc.), SQL, SAS, Python (sklearn, pandas, etc.)
Research Interests
- Multivariate statistics
- Anomaly detection
- Time series
- Machine learning
Education
Baylor University
(2025) Ph.D. in Statistics, GPA: 3.97/4.00
(2022) M.S. in Statistics, GPA: 3.94/4.00
Brigham Young University
(2021) B.S. in Statistical Science, minor in mathematics, GPA: 3.99/4.00