Pamela Pyzza joined Kenyon’s faculty in 2020 after spending five years as a faculty member at Ohio Wesleyan University. As an applied mathematician, her research considers the dynamics of complex network systems with real-world applications in biological and social sciences. Pyzza works in the field of computational neuroscience where she uses mathematical modeling and computer programming to investigate how networks of neurons coordinate to perform complex functions underlying seemingly commonplace neurological aspects of everyday life such as one’s sense of smell and the necessity of sleep. Pyzza believes that effective communication between applied mathematicians and experimental researchers paves the way for robust research and important scientific progress.

Pyzza’s teaching focuses on the theory and methodologies used to model real-world problems, leading students toward a mathematical understanding of phenomena that arise in their own experiences. She emboldens students to take ownership of and pride in their work and to develop strong communication skills.

Areas of Expertise

Dynamical systems, computational neuroscience, biological network modeling

Education

2015 — Doctor of Philosophy from Rensselaer Polytechnic Institu

2010 — Master of Science from Rensselaer Polytechnic Institu

2009 — Bachelor of Science from Rensselaer Polytechnic Institu

Courses Recently Taught

The first in a three-semester calculus sequence, this course covers the basic ideas of differential calculus. Differential calculus is concerned primarily with the fundamental problem of determining instantaneous rates of change. In this course we will study instantaneous rates of change from both a qualitative geometric and a quantitative analytic perspective. We will cover in detail the underlying theory, techniques and applications of the derivative. The problem of anti-differentiation, identifying quantities given their rates of change, also will be introduced. The course will conclude by relating the process of anti-differentiation to the problem of finding the area beneath curves, thus providing an intuitive link between differential calculus and integral calculus. Those who have had a year of high school calculus but do not have advanced placement credit for MATH 111 should take the calculus placement exam to determine whether they are ready for MATH 112. Students who have 0.5 units of credit for calculus may not receive credit for MATH 111. Prerequisite: solid grounding in algebra, trigonometry and elementary functions. Offered every semester.

Special Topic

This course provides a survey of several techniques used in applied mathematics. We will discuss the mathematical formulation of models for a variety of processes that arise in the natural and social sciences. We will derive the appropriate equations to describe these processes and use techniques from calculus, differential equations, linear algebra and numerical methods when needed. This course may touch on topics like dimensional analysis, scaling, kinetic equations and perturbation methods. Students will have the opportunity to investigate applications within their fields of interest such as biology, medicine, physics, chemistry and finance. A strong background in calculus is essential; a familiarity with differential equations is recommended, but not required. Prerequisite: MATH 112 or permission of instructor. Offered every other year.