Elle Weeks joined the Kenyon faculty in 2026. Her research uses mathematical models to better understand Earth's climate, with a particular focus on the physical processes that drive climate variability and change. She works across a range of modeling approaches, from simple analytical models to complex numerical climate simulations.

Weeks enjoys helping students discover how mathematics can be used to answer questions they care about. In her teaching, she emphasizes the connections between mathematical concepts and real-world applications, encouraging students to see mathematics as a powerful tool for understanding the world around them.

Outside of the classroom, Weeks enjoys running, riding bikes and rock climbing, and is always excited to explore new places outdoors.

Areas of Expertise

Mathematical modeling, dynamical systems, climate dynamics

Education

2026 — Doctor of Philosophy from Harvard University

2017 — Bachelor of Arts from Macalester College

Courses Recently Taught

This is the second course calculus sequence, this course focuses on integration, including Riemann sums, the Fundamental Theorem of Calculus, techniques of integration, numerical methods, and applications of integration. This study leads into the analysis of differential equations by separation of variables, Euler's method, and slope fields. This counts toward the core course requirement for the major. Prerequisite: MATH 111 or the equivalent. Offered every semester.

This course examines differentiation and integration in three dimensions. Topics of study include functions of more than one variable, vectors and vector algebra, partial derivatives, optimization, and multiple integrals. Some of the following topics from vector calculus also are covered as time permits: vector fields, line integrals, flux integrals, curl and divergence. This counts toward the core course requirement for the major. Prerequisite: MATH 112 or equivalent. Offered every semester.

Many problems in science and engineering cannot be solved exactly, or even accurately approximated, using analytical methods alone. This course provides an introduction to scientific computing, the use of computational methods to obtain and analyze approximate solutions to mathematical problems. Topics will include numerical differentiation and integration, root finding, data fitting, optimization, and numerical methods for differential equations. Throughout the course, we will develop and analyze computational algorithms, considering questions such as: How can we design an algorithm to solve a given problem? How efficient is the method? How accurate is the resulting approximation? This course counts toward the applied (column D) elective requirement for the major. Prerequisites: MATH 224 and COMP 118.