Department of Mathematics

Faculty and Fields of Interest

Yanlai Chen numerical analysis, scientific computing, reduced order modeling, uncertainty quantification, fractional-order pde’s, data mining, machine learning, applied statistics

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

Gary Davis memory systems in mathematics, mathematics education, statistics and data science education, analystic combinatories, 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-Director of Data Science Interdisciplinary 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 CSCVR) numerical analysis, scientific computing, strong stability preserving methods, weighted essentially non-oscillatory methods, data science, applied statistics

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

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

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

Donghui Yan statistics, machine learning, data mining, distributed inference and learning, imaging and computer vision, deep learning, data science, applied statistics

Cheng Wang numerical analysis, numerical pde’s, data science, applied statistics

Full-Time Lecturers:

Sergei Artamoshin mathematics education

Sara K. Dalton Bildik mathematics education

Melvyn Huff mathematics education

Biyong Luo (Lower Division Math Coordinator) mathematics education

Adriano Marzullo mathematics education

Faculty Emeriti:

Nurit Budinsky applied mathematics

Robert Kowalczyk applied mathematics

Steven J Leon numerical analysis, linear algebra

Gary Martin logic

Robert L McCabe mathematics education

Ronald Tannenwald dynamical systems

About the Department

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

The mathematics program provides a solid foundation in both the theoretical and applied aspects of mathematics and statistics, 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, scientific computing, software development, public health, consulting, marketing, and statistics.

You’ll also be well-prepared for graduate studies in math, statistics, or in 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 five-degree programs in mathematics: BA degree, BS degree, BS degree with a concentration in applied and computational mathematics, BS degree with a concentration in applied statistics. All degrees require completion of 120 credit hours overall.

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 the Center for Scientific Computing and Visualization Research
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

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, modeling, computing, and statistics.

You will learn to how to:

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

We offer both BA and BS degrees in mathematics. Both degrees require 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 a total of 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 6 credits in science courses at the level taken by majors. For the BA degree in mathematics, you should complete an additional 3 credit in science course at the level taken by majors and an additional 6 credits in Foreign Languages through 202 as well. Students must also complete all College Studies and University Studies requirement for their degree.

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

Mathematics BS with Concentration in Applied and Computational Mathematics Option

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

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 a total of 30 credits at the 300 level or higher; these courses include Math, Technical and Science electives. You must complete an additional 6 credits in science courses at the level taken by majors in science courses to earn the BS degree in mathematics. Students must also complete all College Studies and University Studies requirement for their degree.

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

Mathematics BS with Concentration in Applied Statistics

The Applied Statistics concentration is designed to educate and train students in the applications of data analysis and computational statistics. You’ll learn in-depth skills in mathematics and statistics to work as an applied statistician in a variety of industries, government, or nonprofit agencies or for graduate studies. You’ll also gain effective communication skills for the presentation of analysis or results.

A BS degree in mathematics with applied statistics 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.

DSC101 (US 1E: 3 credits)
Math Core Requirements (48 credits)
MTH451 and MTH452 (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 a total of 30 credits at the 300 level or higher; these courses include Math, Technical and Science electives. You must complete an additional 8 credits in science courses at the level taken by majors or 8 credits in both PHY113 and PHY114. Students must also complete all College Studies and University Studies requirement for their degree.

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

Minor in Mathematics

Enhance your career options by earning a minor in mathematics. You’ll develop the analytical and problem-solving 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.

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

Minor in Data Analytics

Enhance your employment prospects through acquisition of sought-after data analytic skills, and enhance your ability to engage more deeply with societal issues through appropriate analysis of relevant data, especially through issues arising in your major. This program is to provide 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 in sciences such as biology and psychology. The Data Analytics minor is focused on providing you with a viable and attractive route to appropriate and useful data analytics education and training, consistent with your major study in a data-driven and data-aware society.

For the minor, you’ll complete the total number of 6 courses with a total number of 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.

Data Science Interdisciplinary Program:

The interdisciplinary Data Science program is designed to combine courses that cover specific topics like data visualization, and matrix methods for data mining, with traditional courses in Mathematics and Computer & Information Science.
In mathematics, students will take statistics, probability, linear algebra, scientific computation, and calculus. 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.
A BS degree in interdisciplinary data science will prepare 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—as well as for graduate programs in Data Science.
Link to the data science program: http://www.umassd.edu/interdisciplinary/datascience/

Continue your 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. Students pursing teacher preparation at UMass Dartmouth graduate 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 towards a license to teach, students should indicate their interest to both their mathematics major advisor and the Coordinator of Teacher Preparation Programs. 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 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

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) & 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 making significant use of mathematics.
Mathematical rigor: Students are able to reason rigorously in mathematical arguments. They can follow abstract mathematical arguments and write their own proofs.
Communication: Students are able to communicate mathematics: reading, writing, listening, and speaking. Students make effective use of the library, conduct research and make oral and written presentations of their findings.
Computers: Students are able to write programs or use mathematical software to explore, visualize, and solve mathematical problems and to verify analytical calculations.
Flexible problem solving: Students are able to transfer facts, concepts, and skills learned in a given context to solve problems in novel settings.