Trevor D. Ruiz

I’m an Assistant Professor in the Statistics Department at Cal Poly SLO. I’m interested in applied statistics, data analysis, collaborative science, and teaching.

Appointments

California Polytechnic State University, San Luis Obispo

Assistant Professor | 2023-present

University of California, Santa Barbara

Visiting Assistant Professor | 2020-2023

Education

Oregon State University

Ph.D. & M.S. Statistics | 2015-2020

Reed College

B.A. Philosophy | 2007-2011

About

I work primarily on statistical methods for the analysis of correlated and high-dimensional data in biology and ecology, and I especially enjoy collaborative applied projects in this area.

I’m eager to work with student collaborators and most of my agenda is designed with this in mind. If you’re interested in working with me, or would like to chat about what that might entail, please get in touch.

The rest of this page represents my most recent work (last 2-3 years) and I typically update it quarterly.

Current projects

[AY24-25] Covariate adjustment and dependent error models in sparse partial least squares for high-dimensional compositional data

Supported by the Research, Scholarly & Creative Activities Program awarded by the Cal Poly Division of Research

Increasingly, ecological surveys encompass sampling and metabarcoding of environmental DNA from water, soil, and other media. Such data can capture rich networks of ecological relationships and, when combined with traditional survey measurements, can be used to explore relationships between ecological communities. However, many if not most statistical approaches to the analysis of metabarcoding data were originally developed in the context of microbiome studies, in which there is substantially less environmental and spatiotemporal variation across samples. As such, few current methods incorporate covariate adjustments for environmental features or error models accounting for dependence between observations across space and time. This project aims to develop such adjustments in the context of partial least squares – a common modeling framework for high-dimensional compositional data – and illustrate their application to ecological data.

Recent work

Listed in reverse chronological order; \(\dagger\) indicates student coauthors.

  • E.M. Reardon\(^\dagger\), N.E. Yee\(^\dagger\), T.D. Ruiz, H.A. Moniz, S.M. Boback, E.N. Taylor. Effects of reproductive status on standard metabolic rate of the prairie rattlesnake (Crotalus viridis) at high elevation site with a short active season. In preparation.

  • E.V. Satterthwaite, T.D. Ruiz, K.G. Chan\(^\dagger\), N. Patrick\(^\dagger\), M.N. Alksne, N.V. Patin, J. Dinasquet, R.H. Lampe, A.O. Shelton, L. Thomas, B. Semmens. Microbial and small plankton indicators of marine mammal abundance. In preparation.

  • T. D. Ruiz, S. Bhattacharyya, S. C. Emerson. Sparse estimation of parameter support sets for generalized vector autoregressions by resampling and model aggregation. Under review. [preprint]

  • H. A. Moniz, J. H. Buck, H. L. Crowell, S. M. Goetz, T. D. Ruiz, S. M. Boback, E. N. Taylor (2024). High thermal quality rookeries facilitate high thermoregulatory accuracy in pregnant female rattlesnakes. Journal of Thermal Biology. [paper] [data] [code]

  • A. M. E. Ojwang', T. D. Ruiz, S. Bhattacharyya, S. Chatterjee, P. S. Ojiambo, D. H. Gent (2021). A general framework for spatio-temporal modeling of epidemics with multiple epicenters: application to an aerially dispersed plant pathogen. Frontiers in Applied Mathematics and Statistics. [paper]

Recent courses

I currently teach courses in probability, applied statistics, and data science. My broader teaching competence includes most areas of statistics at an advanced undergraduate level.

  • [STAT425] Probability theory: Fall 2023, Fall 2024
  • [STAT218] Applied statistics for life sciences: Winter 2024, Spring 2024, Winter 2025, Spring 2025
  • (UCSB) [PSTAT197] Data science capstone: Winter 2022, Spring 2022, Fall 2022, Winter 2023, Spring 2023
  • (UCSB) [PSTAT100] Data science concepts and analysis: Spring 2021, Winter 2022, Spring 2022, Spring 2023

Recent student work

  • N.E. Yee, E.M. Reardon (2024). Modeling the baseline metabolic needs of prairie rattlesnakes (Crotalus viridis) based on reproductive status. 2024 Cal Poly SURP+ Symposium. [poster]

  • K. G. Chan (2024). Using plankton eDNA to estimate whale abundances off the California coast: data integration and statistical modeling. California Polytechnic State University. [thesis]

  • S. Rumsey, E. Ho, C. Zheng, N. Setiawan, J. Park (2023). Identifying case onset points for early detection of influenza-like illness. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD’23). Poster presentation. [abstract]

  • L. Umsted, J. Liu, P. Trujillo, E. Burrell (2023). Understanding and modeling human mobility response to California wildfires. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD’23). Poster presentation. [abstract]

  • M. Gupta, A. Adams (2022). A scrollytelling primer on hypoxia: developing a data storytelling tool to communicate ocean observing data to California citizens. CalCOFI Conference 2022: Innovative Techniques and Novel Applications of Time Series Data to Marine Resource Management. Contributed talk. [scrollytelling project]