CV

Education

Ph.D. Applied Mathematics University of Arizona, Tucson, Arizona. August 2023.
Graduate minor in Systems and Industrial Engineering.
Dissertation: The Estimation of High-contrast Spectra via Iterated Whitening.
Advisor: Kevin Lin.

M.S. Applied Mathematics University of Arizona, Tucson, Arizona. May 2018.
Advisor: Kevin Lin.

M.S. Mathematics Brigham Young University, Provo, Utah. August 2016.
Thesis: Steady State Configurations of Cells Connected by Cadherin Sites.
Advisor: John Dallon.

B.S. Mathematics and Mathematics Education Brigham Young University. April 2012.

Employment

Southern Virginia University, Buena Vista, Virginia Assistant Professor of Math 2023 - present

Mathematics Department, UA, Tucson, Arizona Instructor 2023

Mathematics Department, UA, Tucson, Arizona Graduate Teaching Assistant 2016 - 2022

Chemistry & Biochemistry Department, UA, Tucson, Arizona GRE Preparation Math Tutor for the Maximizing Access to Research Careers (MARC) Program 2016

Mathematics Department, BYU, Provo, Utah Research Assistant to Dr. J. Humphreys 2015 - 2016 Proofread several chapters of Foundations of Applied Mathematics, Volume I: Mathematical Analysis

Mathematics Department, BYU, Provo, Utah Graduate Teaching Assistant 2014 - 2016

Utah Valley University, Orem, Utah Assistant Coordinator in the Mathematics Tutorial Lab 2013 - 2014

Vernal Junior High, Vernal, Utah Math Teacher (8th grade) 2012 - 2013

Teaching

Southern Virginia University

(August 2023 - present)

SemesterCourseUnits
Fall 2025CSC 340: Artificial Intelligence3
Fall 2025MAT 343: Linear Algebra3
Fall 2025MAT 221: Statistics3 (×2)
Fall 2025MAT 115: College Algebra3
Summer 2025MAT 221: Statistics3
Spring 2025CSC 333: Computational Data Science3
Spring 2025MAT 498: Mathematics Capstone1
Spring 2025MAT 221: Statistics3 (×3)
Fall 2024MAT 341: Real Analysis3
Fall 2024MAT 343: Linear Algebra3
Fall 2024MAT 221: Statistics3 (×3)
Spring 2024MAT 410: Introduction to Numerical Analysis3
Spring 2024MAT 341: Calculus III3
Spring 2024MAT 221: Statistics3 (×2)
Spring 2024MAT 116: Trigonometry1
Spring 2024MAT 115: College Algebra3
Fall 2023MAT 343: Linear Algebra3
Fall 2023MAT 221: Statistics3 (×2)
Fall 2023MAT 115: College Algebra3

Department of Mathematics, University of Arizona

(Fall 2016 - Spring 2023)

SemesterCourseUnits
Spring 2023Math 116: Business Calculus3 (×2)
Spring 2022Math 196V: Vector Calculus Supplement1
Fall 2021Math 196V: Vector Calculus Supplement1
Spring 2021Math 129: Second Semester Calculus3
Fall 2020Math 122B: First Semester Calculus4
Spring 2020Math 122A: Functions of Calculus1 (×2)
Fall 2019Math 122A: Functions of Calculus1 (×2)
Spring 2019Math 122A: Functions of Calculus1 (×2)
Fall 2018Math 120R: Precalculus4
Summer 2018Math 116: Business Calculus (online)3
Spring 2018Math 116: Business Calculus3
Fall 2017Math 120R: Precalculus4
Spring 2017Math 116: Business Calculus3
Fall 2016Math 112: College Algebra3 (×2)

Department of Mathematics, Brigham Young University

(Spring 2014 - Summer 2015)

SemesterCourseUnits
Fall 2015Math 110: College Algebra3
Summer 2015Math 112: Calculus I4
Winter 2015Math 102: Quantitative Reasoning3
Fall 2014Math 110: College Algebra3
Spring 2014Math 102: Quantitative Reasoning3

Teaching Assistant

In all courses I assisted the instructor in varying capacities ranging from grading, holding office hours, holding problem sessions, etc.

Department of Mathematics, University of Arizona

(Fall 2018 - Spring 2022)

SemesterCourseInstructor
Spring 2022Math 485: Intro to Mathematical ModelingJoceline Lega
Spring 2022Math 584B: Principles of AnalysisShankar Venkataramani
Fall 2021Math 584A: Principles of AnalysisShankar Venkataramani
Spring 2021Math 527B: Principles of AnalysisShankar Venkataramani
Fall 2020Math 527A: Principles of AnalysisShankar Venkataramani
Spring 2020Math 527B: Principles of AnalysisShankar Venkataramani
Fall 2019Math 527A: Principles of AnalysisShankar Venkataramani
Summer 2019Co-facilitated program sponsored qualifying exam prep course
Spring 2019Math 527B: Principles of AnalysisLeonid Friedlander
Summer 2018Co-facilitated program sponsored qualifying exam prep course
Fall 2018Math 527A: Principles of AnalysisLeonid Friedlander

Course Development

Artificial Intelligence (Southern Virginia University CSC 340, upper division computer science course artificial intelligence) I developed the curriculum to focus on developing deep conceptual understanding of neural networks (including backpropagation) as well as implementation of these concepts in Python using libraries. Though it spends most of the time looking at supervised learning, unsupervised learning (PCA and $k$-means) as well as some reinforcement learning is also discussed. The course also includes a significant ethics component.

Computational Data Science (Southern Virginia University CSC 333, upper division computer science course computational data science) I developed the curriculum to focus on developing practical skills in data science using Python. The course covers data cleaning, visualization, and analysis using libraries such as Pandas, Matplotlib, Seaborn, and some Scikit-learn. The big concept discussed was multiple regression and how to interpret the results of a regression analysis.

Mathematical Modeling (University of Arizona Math 485, senior level project-based course mathematical modeling) I assisted Dr. Joceline Lega in converting the course to an asynchronous, fully online format. My principle task was to use Manim (a Python package for programmatic mathematical animation) to create animation to improve the accessibility of the interactive video presentations.

Mentoring

Southern Virginia University

Department of Mathematics, University of Arizona

Service

Research Interests

General: Data-driven model reduction, signals and systems theory, stochastic models and stochastic differential equations, power distribution systems with renewable energy sources, smart grids, cell movement, urban traffic.

Current projects: Applying classical signal processing theory to data-driven model reduction, power spectrum estimation, Model reduction for power systems networks, and modeling movement of the slime mold Dictyostelium discoideum.

Publications

Jared McBride and Kevin K Lin, A comparison of spectral estimation methods for the analysis of chaotic and stochastic dynamical systems. In preparation, 2023.

Darin J Law, Jason P Field, Luke A Wilson, Mallory F Barnes, David D Breshears, Jared McBride, Greg A Barron-Gafford, Angelina Martínez-Yrízar, Alberto Búrquez, and Enriquena Bustamante Ortega. Heatwave compounded warmer drought: Shifts in time to tree mortality and tree mortality duration. In preparation, 2023.

Conferences

Third Symposium on Machine Learning and Dynamical Systems, September 26 - 30, 2022, The Fields Institute, Toronto, Canada Presented poster: A comparison of spectral estimation methods for the analysis of chaotic and stochastic dynamical systems

Volunteer Community Involvement

Church of Jesus Christ of Latter-day Saints Full-time Missionary. Manchester, England, 2007-2009

Central Utah STEM Fair Judge. Provo, Utah, 2014

ACCESS (BYU big brother/big sister program) big brother volunteer. Provo, Utah, 2014

$\pi$-Day volunteer. Provo, Utah, 2014-2016

S.Y.STEM Coalition Science Day volunteer. Tucson, Arizona, 2016

S.Y.STEM Coalition Summer Robotics Camp facilitator assistant. Tucson, Arizona, 2019

Church of Jesus Christ of Latter-day Saints recent involvement in local congregation (ward). Tucson, Arizona,

Skills

Git, Julia, Python, Manim (Python package for programmatic mathematical animation).