About

I am a first year PhD student at the Carnegie Mellon University Department of Statistics and Data Science where I am a member of the Statistical Methods for the Physical Sciences group currently working with Mikael Kuusela and Donata Giglio on improved uncertainty quantification for ocean heat content.

Interests

• Statistics in the physical sciences
• Methods for spatio-temporal data
• Uncertainty quantification
• Statistical computing

Research

While pursuing a BS in Applied Mathematics at Boise State University (2018-21):

• The animaltracker R package for spatio-temporal analysis, visualization, and validation of animal data (CRAN/GitHub/ScholarWorks)
• Open-source tools for ambient seismic noise cross-correlation parallelized in Julia on the cloud (GitHub/Seismological Society of America Annual Meeting 2020)
• Exploring parametric approaches to model soccer team goals in European leagues (GitHub/Carnegie Mellon Sports Analytics Conference 2020)
• Seasonal trend and changepoint analysis of United States extreme precipitation (joint senior thesis with Meghan Edgerton, advised by Jaechoul Lee)
• Exploring the robustness of deep learning architectures on ICU mortality prediction (University of Michigan Department of Biostatistics Big Data Summer Institute 2019)

Teaching Assistant Experience

Carnegie Mellon University:

• 36-468/668 Text Analysis
• 36-350 Statistical Computing

Boise State University:

• MATH 361 Probability & Statistics I
• MATH 360 Engineering Statistics
• MATH 254 Introduction to Statistics
• MATH 154 Statistical Reasoning

Contact

• Email: thea(at)stat.cmu.edu

(Note: I am not available for private tutoring.)