Nastaran Naghshineh Headshot

Nastaran Naghshineh

Lecturer of Mathematics

RIT Dubai

00971-4-3712089

Nastaran Naghshineh

Lecturer of Mathematics

RIT Dubai

00971-4-3712089

Select Scholarship

Journal Paper
Naghshineh, Nastaran, et al. "The Shape of an Axisymmetric Meniscus in a Static Liquid Pool: Effective Implementation of the Euler Transformation." IMA Journal of Applied Mathematics. (2024): 1-30. Web.
Naghshineh, Nastaran, et al. "On the Use of Asymptotically Motivated Gauge Functions to Obtain Convergent Series Solutions to Nonlinear ODEs." IMA Journal of Applied Mathematics. (2023): 43-66. Print.
Naghshineh, Nastaran, et al. "Asymptotically-consistent Analytical Solutions for the non-Newtonian Sakiadis Boundary Layer." Physics of Fluids. (2023): 1-15. Web.

Currently Teaching

MATH-101
3 Credits
This course provides the background for an introductory level, non-trigonometry based calculus course. The topics include a review of the fundamentals of algebra: solutions of linear, fractional, and quadratic equations, functions and their graphs, polynomial, exponential, logarithmic and rational functions, and systems of linear equations.
MATH-161
4 Credits
This course is an introduction to the study of differential and integral calculus, including the study of functions and graphs, limits, continuity, the derivative, derivative formulas, applications of derivatives, the definite integral, the fundamental theorem of calculus, basic techniques of integral approximation, exponential and logarithmic functions, basic techniques of integration, an introduction to differential equations, and geometric series. Applications in business, management sciences, and life sciences will be included with an emphasis on manipulative skills.
MATH-241
3 Credits
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.

Website last updated: July 17, 2024