About


Currently, I am an Assistant Professor of Mathematics in the Natural Science Division of Seaver College at Pepperdine University, though broadly, I would describe myself as an educator and scholar. Teaching mathematics is my passion and I am continually striving to become a more effective teacher by applying new tools and skills to motivate students both inside and outside of the classroom. My research focus lies in network theory and network analysis where, specifically, I work on the development of computational and statistical techniques to model, analyze, and explore complex, relational data. To learn more about my professional experience, along with my teaching philosophy, research background, and diversity stance, please hover over the nodes on the adjacent network!

Contact


Email
christina.duron@pepperdine.edu

Office Telephone
(310) 506 - 4832

Office
RAC 105

Office Hours (Spring 2023)
Monday and Friday: 2:00PM - 3:00PM
Tuesday and Thursday: 10:30AM - 11:30AM
Or by appointment
(All times are in PST)

Recent Publications


  1. Fider N, Durón C., Pfeffer D. (2022). From Mirrors to Wallpapers: A Virtual Math Circle Module on Symmetry. Journal of Math Circles: Vol 3: Iss. 1, Article 1.


  2. Durón C. (2022). Adaptive Quadrature. In Wiley StatsRef: Statistics Reference Online (eds N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri and J.L. Teugels). doi: 10.1002/9781118445112.stat08388


  3. Durón C., Farrell A. (2022). A Mean-Field Approximation of SIR Epidemics on an Erdös-Rényi Network Model. Bulletin of Mathematical Biology: 84(7), 1-19. doi: 10.1007/s11538-022-01026-2

Dissertation: Durón C. The Distribution of Betweenness Centrality in Exponential Random Graph Models. ProQuest on May 18, 2019.


Alternatively, my publications can be found on my Google Scholar profile.

Current Course Information


Announcements
Nothing yet.

Course Overview
Math 150 provides an introduction to first-semester calculus, from rates of change to integration, with an emphasis on understanding, problem solving, and modeling. Topics covered include key concepts of the derivative and definite integral, techniques of differentiation, and applications.

Syllabus

Note: The posted files (assignments and lecture notes) are only accessible to those within Pepperdine University.

Assignments
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10
Week 11
Week 12
Week 13
Week 14

Lecture Slides

Announcements
Nothing yet.

Course Overview
Math 260 provides an introduction to Linear Algebra, covering much of Chapters 1 – 7. Topics covered include systems of linear equations and linear transformations; matrix determinant, inverse, rank, eigenvalues, eigenvectors, factorizations, diagonalization, singular value decomposition; linear independence, vector spaces and subspaces, bases, dimensions; inner products and norms, orthogonal projection, Gram-Schmidt process, least squares; applications.

Syllabus

Note: The posted files (assignments and lecture notes) are only accessible to those within Pepperdine University.

Assignments
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10
Week 11
Week 12
Week 13
Week 14

Lecture Slides

Past Courses


Fall 2022 – Pepperdine University

Course Overview
Math 150 provides an introduction to first-semester calculus, from rates of change to integration, with an emphasis on understanding, problem solving, and modeling. Topics covered include key concepts of the derivative and definite integral, techniques of differentiation, and applications.

Syllabus


Fall 2021 – University of Arizona

Course Overview
MATH 464 provides an introduction to the theory of probability, the part of mathematics that studies random phenomena. We model simple random experiments mathematically and learn techniques for studying these models. Topics covered include probability spaces, random variables, weak law of large numbers, central limit theorem, various discrete and continuous probability distributions.

Syllabus


Spring 2021 – University of Arizona

Course Overview
DATA/MATH 363 will be using your background in the natural or social sciences, the humanities, or engineering and your previous knowledge of algebra, calculus and linear algebra to consider the issues of collection, model derivation and analysis, interpretation, explanation, and presentation of data. The objective of this course is to take advantage of the coherent body of knowledge provided by statistical theory having an eye consistently on the application of the subject. This approach will allow you to extend your ability to use methods in data science beyond those given in the course.

Syllabus


Fall 2020 – University of Arizona

Course Overview
This course is a continuation of MATH 122B or MATH 125 that will examine the techniques of symbolic and numerical integration, applications of the definite integral to geometry, physics, economics, and probability; differential equations from a numerical, graphical, and algebraic point of view; modeling using differential equations, approximations by Taylor series.

Syllabus

Course Overview
This course acts as an introduction to the basic techniques of numerical analysis and provides insight into both the theory and algorithms for fundamental mathematical problems associated with systems of equations, optimization, and approximation of functions. The course assumes familiarity with linear algebra and calculus, and requires the use of the programming language, MATLAB.

Syllabus


Spring 2020 – University of Arizona

Course Overview
Statistics is the field of study involving (1) the collection, summarization, and analysis of data; and (2) the drawing of inferences about a population from the examniation of a sample of the population. The goals of this course are to introduce each student to the practice of statistics and to provide an overview of common topics in statistical inference.

Syllabus


Fall 2019 – University of Arizona

Course Overview
MATH 122B is a 4-unit course, during which students will be challenged to develop their calculus-related understanding, problem-solving, and modeling skills.

Syllabus

Course Overview
This course is designed as a complement to MATH 120R. Students enrolled in the course will participate in a weekly problem session pertaining to material covered in MATH 120R. Concurrent registration in MATH 120R is required.

Syllabus

Course Calendar


MATH 150
MATH 260