Department of Mathematics

About the Department

Mathematicians are problem solvers, critical thinkers, and uncertainty quantifiers, applying their knowledge and skills in academia, government, industry, research, technology, and health organizations or agencies..

The mathematics program provides a solid foundation in mathematics and statistics’ theoretical and applied aspects. The program prepares a major for various careers, including actuarial science, algorithm design, computer information systems, data science, economics, education, finance, government, law, insurance, manufacturing, medicine, psychology, scientific computing, software development, public health, and consulting, marketing, and statistics.

You will also be well-prepared for graduate studies in math, statistics, or areas that emphasize logical reasoning, math, or statistics, such as economics, engineering, the physical sciences, the life sciences, the social sciences, and the law.

We offer four-degree programs majoring in mathematics:

BA degree (MTH-BA)
BS degree (MTH-BS)
BS degree with a concentration in applied and computational mathematics (MTH-BS-Applied & Computational Math)
BS degree with a concentration in applied statistics (MTH-BS-Applied Statistics)

All degrees require completion of 120 credit hours overall.

We also offer a minor in mathematics (MTH-MN) and a minor in data analytics (DAN-MN). All minor degrees require completion of 24 credit hours overall.

In addition, we offer a data science interdisciplinary degree (DSC-BS) program.

Mathematics Curriculum

Our curriculum offers flexibility, allowing you to concentrate on your areas of interest. You will have a wide selection of courses, including algebra, calculus, computational mathematics, geometry, probability, simulations, modeling, computing, and statistics.

You will learn and acquire how to:

Understand core mathematical or statistical skills.
Form logical arguments with correct reasoning.
Infer valued results with data-driven analysis.
Recognize the connection between different areas of mathematics or statistics and understand relationships between ideas.
Link applications and theory.
Utilize modern technological tools.

Student Learning Outcomes

Content knowledge and skills: Students possess specific technical/analytical skills and conceptual understanding in core areas of mathematics, including calculus, linear algebra, combinatorics, differential equations, advanced calculus (analysis), probability, mathematical statistics, complex analysis & modern algebra.
Context and modeling: Students connect different areas of mathematics with other disciplines; they effectively use the interplay between applications and problem-solving, applying what they know from one realm to answer questions from another. Students use concepts and skills from the core areas to formulate mathematical models and solve multi-step problems. Students demonstrate knowledge of a discipline by making effective use of mathematics.
Mathematical rigor: Students can reason rigorously in mathematical arguments. They can follow abstract mathematical arguments and write their proofs.
Communication: Students can communicate mathematics: reading, writing, listening, and speaking. Students effectively use the library, conduct research, and make oral and written presentations of their findings.
Computers: Students can write programs or use mathematical software to explore, visualize, solve mathematical problems and verify analytical calculations.
Flexible problem solving: Students can transfer facts, concepts, and skills learned in a given context to solve problems in novel settings.

Special opportunities

Undergraduate Research: engage in research projects with expert faculty mentors and present students’ work at national and international conferences.
Undergraduate Teaching: hone math skills and become peer mentors as tutors, undergraduate teaching assistants, or supplement instructor leaders for lower-level math courses.
Merit Scholarships: receive one of four designated math merit scholarships, Gertrude Keigher Scholarship, Samuel Stone Scholarship, Jennie Szymanski Mierzejewski Scholarship, and Professor Louis & Margaret Simeone Scholarship.
New Initiatives: collaborate, create, and explore at the Center for Scientific Computing and Data Science Research (CSCDR).
Community: participate in our Chapter of the Society for Industrial and Applied Mathematics or the student-led group, Mathematics and Physics Opportunities for Women in Research.

You can find detailed info regarding the Mathematics Department at the site https://www.umassd.edu/cas/math/.

Mathematics BA & BS

Both degrees require the completion of 120 credit hours of overall coursework. These credits consist of the following:

Math Core Requirements (39 credits)
MTH421/MTH451 and MTH465 (US 5A and 5B requirements) (6 credits)
Required Physics courses PHY113 and PHY114 (8 credits)
Math electives - 300 level or above (9 credits)

Students must complete 30 credits at the 300 level or higher; these courses include Math, Technical, and Science electives. For the BS degree in mathematics, you should complete an additional six credits in science courses at the level taken by majors. For the BA degree in mathematics, you should complete an additional three credits in a science course at the level taken by majors and an additional six credits in Foreign Languages through 202. A student must also complete degree’s College Studies and University Studies requirements.

You can find detailed info regarding the mathematics program at the site http://www.umassd.edu/cas/math/undergraduate-programs/.

Mathematics BS with Concentration in Applied and Computational Mathematics

With a core of computation-oriented courses, the applied and computational mathematics concentration emphasizes applied mathematics 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.

This concentration will prepare you for employment in fields where physical and industrial problems are analyzed mathematically and for graduate programs in computation-oriented mathematics.

This concentration requires the completion of 120 credit hours of overall coursework. These credits consist of the following:

Math Core Requirements (39 credits)
MTH475 and MTH440 (US 5A and 5B requirements: 6 credits)
Required Physics courses PHY113 and PHY114 (8 credits)
Math electives - 300 level or above (9 credits) in addition to the required mathematics courses
Technical elective – any major-level course in CIS, Physics, or Engineering (3 credits)

Students must complete 30 credits at the 300 level or higher; these courses include Math, Technical, and Science electives. You must complete an additional six credits in science courses at the level taken by majors in science courses to earn the BS degree in mathematics. A student must also complete degree’s College Studies and University Studies requirements.

You can find detailed info regarding the mathematics program at the site http://www.umassd.edu/cas/math/undergraduate-programs/.

Mathematics BS with Concentration in Applied Statistics

The Applied Statistics concentration educates and trains students in the applications of data analysis and computational statistics. You will learn in-depth skills in mathematics and statistics to work as an applied statistician in various industries, government, or nonprofit agencies or for graduate studies. You will also gain effective and practical communication skills for the presentation of analysis or results.

This concentration will prepare you for employment in fields where statistical methods and techniques are needed. You can also continue to pursue an advanced degree in statistics-oriented mathematics.

This concentration requires the completion of 120 credit hours of overall coursework. These credits consist of the following:

DSC101 (US 1E: 3 credits)
Math Core Requirements (48 credits)
MTH431 and MTH432 (US 5A and 5B requirements: 6 credits)
PHL215 (US 4A: 3 credits)
Math/CIS/DSC electives (9 credits) in addition to the required mathematics courses

Students must complete 30 credits at the 300 level or higher; these courses include Math, Technical, and Science electives. You must complete an additional eight credits in science courses at the level taken by majors or eight credits in both PHY113 and PHY114. A student must also complete degree’s College Studies and University Studies requirements.

You can find detailed info regarding the mathematics program at the site http://www.umassd.edu/cas/math/undergraduate-programs/.

Minor in Mathematics

Earning a minor in mathematics enhances your career options. You will develop and acquire the analytical and problem-solving skills essential in many employment settings.

This minor requires completing 24 credit hours of overall math coursework, including nine credits at the 300 level or higher.

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

You can find detailed info regarding the mathematics program at the site http://www.umassd.edu/cas/math/undergraduate-programs/.

Minor in Data Analytics (DAN)

Earning a minor in data analytics enhances your employment prospects by acquiring sought-after data analytic skills. It enhances your ability to engage more deeply with societal issues through appropriate analysis of relevant data, especially through issues arising in your major. This program prepares an entry into data analytics for you who desire to engage in more quantitative ways with your major, particularly in social sciences such as crime and justice, economics and political science, and sciences such as biology and psychology. This minor provides a viable and attractive route to appropriate and valuable data analytics education and training, compatible with your major study in a data-driven and data-aware society.

This minor requires completing 24 credit hours of overall coursework, including 4 DAN courses of 12 credit hours.

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

You can find detailed info regarding the mathematics program at the site http://www.umassd.edu/cas/math/undergraduate-programs/.

Data Science BS Interdisciplinary Program

The interdisciplinary data science program prepares you for a fast-emerging interdisciplinary field that will shape industries and issues such as health care, ocean modeling, climate change, land-use planning, and transportation system design. This program also lays a solid foundation for graduate programs requiring data-driven analysis.

The interdisciplinary data science program combines courses covering specific topics like data visualization and matrix methods for data mining with traditional Mathematics and Computer & Information Science courses. Students will take statistics, probability, linear algebra, scientific computation, and calculus from mathematics. In computer science, students will take courses in object-oriented programming, software design, algorithms, data mining, and machine learning.

In addition, students in their senior year will work in teams on real-world sponsored capstone projects.

You can find detailed info regarding the mathematics program at the site: https://www.umassd.edu/data-science/.

Continue Education with Graduate Studies

Master of Arts in Teaching Mathematics: Enrollment in the 4+1 (BA/BS-MAT) Teacher Preparation program allows undergraduate students to explore teaching as a profession through completion of graduate-level education coursework and field experiences within local public school settings. A student pursuing teacher preparation at UMass Dartmouth graduates with a Bachelor’s degree in their chosen major, a Master’s degree in Teaching, and a Sheltered English Immersion endorsement. In order to develop a plan toward a license to teach, students should indicate their interest to their mathematics major advisor and the Coordinator of Teacher Preparation Programs by entering junior academic standing. Students may enroll in the 4+1 program once they have earned 30 credits with a 3.0 GPA or above.
Master of Science in Data Science: Through a joint initiative with the Computer and Information Science department, we offer a Master of Science degree in Data Science.
Ph.D. in Computational Science and Engineering: Earn an advanced degree in computational science through our Engineering and Applied Science program.
Ph.D. 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.

Faculty and Fields of Interest

Sergei Artamoshin mathematics education

Sara K. Dalton Bildik mathematics education

Nurit Budinsky (Emeritus) applied mathematics

Yanlai Chen (Chief Research Officer) numerical analysis, scientific computing, reduced order modeling, uncertainty quantification, fractional-order pdes, data mining, machine learning, applied statistics

Zheng Chen numerical analysis, scientific computing, high-order numerical methods, fractional pdes, post-processing techniques, uncertainty quantification, applied statistics

Gary Davis memory systems in mathematics, mathematics education, statistics and data science education, analytic combinatorics, text mining, computational linguistics, applied statistics

Bo Dong numerical analysis, scientific computing, discontinuous Galerkin finite element methods, data science, applied statistics

Scott E Field (Co-Graduate Program Director of EAS Ph.D. Program) gravitational wave data science, discontinuous Galerkin methods, scientific computation, computational general relativity, numerical analysis, applied statistics

Dana Fine applied mathematics, quantum gauge theory, supersymmetric quantum mechanics, applied statistics

Sigal Gottlieb (Chancellor Professor, Co-Director of CSCDR) numerical analysis, scientific computing, strong stability preserving methods, weighted essentially non-oscillatory methods, data science, applied statistics

Adam O Hausknecht (Emeritus, Part-Time Math Computer Technician) software for mathematics education, computer graphics, scientific computation, discrete mathematics, universal algebra, data science, applied statistics

software for mathematics education, computer graphics, scientific computation, discrete mathematics, universal algebra, data science, applied statistics

Alfa Heryudono (Co-Graduate Program Director of EAS Ph.D. Program) radial basis functions, spectral and pseudospectral methods, numerical conformal mapping, tear film dynamics, industrial mathematics, numerical pdes, data science, applied statistics

Melvyn Huff mathematics education

Saeja O. Kim (Chairperson) computational algebra, discrete mathematics, edge detection, applied mathematics, topological data analysis, mathematics education, data science, applied statistics

Robert Kowalczyk (Emeritus) applied mathematics

Steven J Leon (Emeritus) numerical analysis, linear algebra

Biyong Luo (Lower Division Math Coordinator) mathematics education

Gary Martin (Emeritus) logic

Adriano Marzullo mathematics education

Harun Omer mathematics education

Ronald Tannenwald (Emeritus) dynamical systems

Vijay Varma gravitational wave astronomy, numerical relativity, data driven modeling, black hole astrophysics

Donghui Yan (Co-Program Director of Data Science Interdisciplinary Program) statistics, machine learning, data mining, distributed inference and learning, imaging and computer vision, deep learning, data science, applied statistics

Cheng Wang numerical analysis, numerical pdes, data science, applied statistics