Department of Mathematics

Faculty and Fields of Interest

Nurit Budinsky nonlinear DEs/dynamical systems, numerical analysis

Yanlai Chen numerical analysis, scientific computing, model reduction, approximation theory, discontinuous Galerkin finite element methods, adaptivity, data science

Gary Davis memory systems, DEs, mathematics education, data science education

Bo Dong numerical analysis and scientific computing, discontinuous Galerkin methods, hybridizable finite element methods, multiscale finite element methods

Dana Fine quantum gauge theory, supersymmetric quantum mechanics

Sigal Gottlieb (Director of CSCVR) strong stability preserving and positivity preserving time discretizations, spatial discretization for hyperbolic problems, spectral and pseudospectral methods, WENO and ENO methods, reduced basis methods, high performance parallel computing, data science

Adam O Hausknecht mathematics software, analysis of algorithms, universal algebra, category theory

Alfa Heryudono radial basis functions, spectral and pseudospectral methods, numerical conformal mapping, tear film dynamics, numerical pdes, data science

Saeja O. Kim (Chairperson) computational algebra, edge detection, applied mathematics, mathematics education, data science eduacation

Akil Narayan numerical analysis and scientific computing, uncertainty quantification for stochastic systems, spectral methods, and orthogonal polynomials, computer vision and shape analysis

Donghui Yan statistics, machine learning, data science

Cheng Wang numerical analysis, numerical PDEs

Lecturer:

Melvyn Huff mathematics education

Biyong Luo (Director of First Year Math Program) mathematics education

James Soden mathematics education

Faculty Emeriti:

Steven J Leon numerical analysis, linear algebra

Gary Martin logic

Ronald Tannenwald dynamical systems

About the Department

Mathematicians are problem solvers and precise thinkers, applying their knowledge and skills in academia, government, industry, research, and technology.

The mathematics program provides a solid foundation in both the theoretical and applied aspects of mathematics, preparing you for a variety of careers including actuarial science, algorithm design, computer information systems, data science, economics, education, finance, government, insurance, manufacturing, medicine, psychology, science computing, software development, and statistics.

You’ll also be well-prepared for graduate studies in math or in areas that emphasize math, such as economics, engineering, and the sciences.

Special opportunities

Undergraduate research: engage in research projects with expert faculty mentors and present your work at national and international conferences
New initiatives: collaborate, create, and explore at our IDEAStudio and the Center for Scientific Computing and Visualization Research
Community: participate in our chapter of the Society for Industrial and Applied Mathematics or the studentled group, Mathematics and Physics Opportunities for Women in Research

Mathematics Major

Our curriculum offers flexibility, allowing you to concentrate in your areas of interest. You’ll have a wide selection of courses to choose from, including algebra, calculus, computational mathematics, geometry, probability, simulations, and statistics.

You will learn to how to:

Understand core mathematical skills 
Form logical arguments with correct reasoning
Recognize connection between different areas of mathematics and understand relationships between ideas

For the major, you’ll complete 59 credit hours in courses related to mathematics or physics, and 6 credits in English, 6 credits in Literature, and an additional 27 credits in upper level courses.

We offer both BA and BS degrees in mathematics. Both degrees require completion of 122 credit hours of overall coursework.

You’ll take an additional 6/3credits in natural science courses to earn the BS/BA degree in mathematics. The humanities/social science requirements for the BS/BA degree are a combined total of 18/21credits.

Computational Mathematics Option

With a core of computation-oriented courses, the computational mathematics option emphasizes applied mathematics that is needed to devise, analyze and implement methods to obtain accurate numerical solutions to applied problems.

In fields such as economics, engineering, finance, the sciences and the social sciences, the equations used to model natural phenomena are too complicated to find exact solutions. To obtain accurate numerical solutions to these equations, computational mathematicians develop and analyze algorithms to run on high performance computers.

A BS degree in computational mathematics will prepare you for employment in fields where physical and industrial problems are analyzed mathematically—as well as for graduate programs in computation oriented mathematics.

For the computational mathematics option, you’ll complete 59 credit hours in mathematics, physics and computer science, and 121 credit hours overall.

Minor in mathematics

Enhance your career options by earning a minor in mathematics. You’ll develop the analytical and problemsolving skills that are essential in many employment settings.

For the minor, you’ll complete 24 credit hours.

A minor must be completed at the time of the degree and will be so noted on the student’s transcript. A student cannot be readmitted to the University to complete only a minor.

Continue your education with graduate studies

Master of Arts in Teaching Mathematics: The department works with the School of Education to prepare highly qualified teachers, providing opportunities for students to receive professional licensure as a Teacher of Mathematics, Grades 8-12.
Master of Science in Data Science: Through a joint initiative with the Computer and Information Science department, we will be offering a Master’s degree in Data Science.
PhD in Computational Science and Engineering: Earn an advanced degree in computational science through our Engineering and Applied Science program.
PhD in Mathematics Education: Our STEM Education and Teacher Development department offers a doctoral program. The program focuses on interdisciplinary perspectives in mathematics education research, Grades K-16.

Student Learning Outcomes

Students should know, be able to recall and use, basic ideas from their core mathematics courses.
Students should be able to determine independently that their work, including calculation and argument, is correct. This includes developing regular habits of checking solutions, verifying answers, and checking for correct calculations and correct reasoning.
Students should formulate answers to mathematical problems. This includes correct and clearly presented English, logical and clearly laid-out solutions, and clear and well-labeled diagrams where appropriate. Students should be able to argue logically and correctly, and be able to produce proofs for mathematical assertions.
Students should have familiarity with graphing calculators and mathematics software including Mathematica Python, MATLAB, or Maple. Students should know how to use mathematical technology appropriately to enhance, not to replace, basic skills and understanding of concepts.
Students should be flexible problem solvers. They should be able to recall basic facts, concepts, and skills, and use them in context, and should be able to use those same facts, concepts, and skills in novel problem settings.
Students should be able to see connections between different areas of mathematics, and understand relationships between ideas.
Students should learn to communicate mathematics effectively.