Richard Cangelosi, Ph.D.

Associate Professor of Mathematics

As an applied mathematician interested in modeling nonlinear phenomena, my focus is on applications related to the life sciences. I enjoy working collaboratively with 91勛圖厙 undergraduates on research projects involving population dynamics, biological...

Portrait of Dr. Richard Cangelosi, Assistant Professor of Mathematics

Contact Information

  • Office Hours Fall 2024

    Tues/Thur: 1:30-3:00 PM office Herak 308B

     



  • (509) 313-3919

Education & Curriculum Vitae

Ph.D. Mathematics, Washington State University

M.S. Mathematics, University of Arizona

B.S. Mathematics, Drexel University

Courses Taught

MATH 148 Survey of Calculus

MATH 157 Calculus-Analytic Geometry I

MATH 258 Calculus-Analytic Geometry II

MATH 260 Ordinary Differential Equations

MATH 413 Real Analysis I

MATH 414 Real Analysis II

MATH 452 Selected Topics (Nonlinear ODEs and Chaos)

MATH 453 Selected Topic (Research Methods in Biomathematics)

MATH 454 Partial Differential Equations

ENSC 244 Computer Methods for Engineers

ENSC 371 Advanced Engineering Math

CPSC 455 Chaos & Dynamical Systems


As an applied mathematician interested in modeling nonlinear phenomena, my focus is on applications related to the life sciences. I enjoy working collaboratively with 91勛圖厙 undergraduates on research projects involving population dynamics, biological pattern formation, delay equations, perturbation theory, chaos theory and the fractal geometry of strange attractors.

Teaching Philosophy

I believe that the primary goal of mathematics instruction is to nurture the growth and development of students' mathematical reasoning. In the process of achieving a level of computational proficiency that may be necessary for the mastery of a given topic, it is essential for students to progress from a procedural to a conceptual way of thinking. I hope to help students move beyond problem solving by way of mimicking examples, to one where an appreciation is gained for the creative aspects inherent in mathematical pursuits and to possibly see the beauty of the logical structure that underlies the subject. Foremost among my goals is to help students become independent learners.

Capobianchi, M., Cangelosi, R., and McGah, P. M. (2021). ASME. J. Heat Transfer. March 2021; 143(3): 031801.

Cangelosi, Richard.
Wolfram Demonstrations Project. Published: June 4, 2021

Cangelosi, R. A.., Schwartz, E., & Wollkind, D. J. A quasi-steady-state approximation to the basic viral dynamics model with a noncytopathic effect. Frontiers in Microbiology: Infectious Disease. Accepted Jan. 10, 2018.

Davis, M. G., Wollkind, D. J., Cangelosi, R. A., & Kealy-Dichone, B. J. (2018) The behavior of a population interaction-diffusion equation in its subcritical regime. Involve: A Journal of Mathematics, 11, 297–309.

Chaiya, I., Wollkind, D. J., Cangelosi, R. A., Kealy-Dichone, B. J., & Rattanakul (2015) Vegetative rhombic pattern formation driven by root suction for an interaction-diffusion plant-ground water model system in an arid environment. American Journal of Plant Science, 6, 1278-1300.

Kealy-Dichone, B., Wollkind, D.J., Cangelosi, R. A. (2015) Rhombic analysis extension of a plant-surface water interaction-diffusion model for hexagonal pattern formation in an arid flat environment. American Journal of Plant Science, 6, 1256-1277.

Cangelosi, R. A., Wollkind, D. J., Kealy-Dichone, B. J., Chaiya, I. (2015) Nonlinear Turing patterns for a mussel-algae model, J. Math. Biol., 7, 1249-94.

Cangelosi, R. A., Olson, J., Madrid, S., Cooper, S., & Hartter, B. (2013) The negative sign and exponential expressions: Unveiling students’ persistent errors and misconceptions. Journal of Mathematical Behavior, 32, 69-82.

Schwartz, E. J., Pawelek, K. A., Harrington, K., Cangelosi, R. A., & Madrid, S. A. (2013) Immune Control of Equine Infectious Anemia Virus Infection by Cell-Mediated and Humoral Responses. Applied Mathematics, 4, 171-177.

Cangelosi, R. & Goriely, A. (2007) Component retention in a principal component analysis with application to cDNA microarray data, 2:Biology Direct 2, .