May 28, 2020  
2018-2019 UMass Dartmouth Undergraduate Catalog 
2018-2019 UMass Dartmouth Undergraduate Catalog [Archived Catalog]

Department of Mathematics

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Faculty and Fields of Interest

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

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

Gary Davis memory systems in mathematics, mathematics education, statistics and data science education, analystic combinatories, text mining, computational linguistics

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

Scott E Field (Co-Director of Data Science Interdisciplinary Program) gravitational wave data science, discontinuous Galerkin methods, scientific computation, computational general relativity, numerical analysis

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

Sigal Gottlieb (Co-Director of CSCVR) numerical analysis, scientific computing, strong stability preserving methods, weighted essentially non-oscillatory methods, data science

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

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

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

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

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


Full-Time Lecturers:

Sergei Artamoshin mathematics education

Sara K. Dalton Bildik mathematics education

Melvyn Huff mathematics education

Biyong Luo (Director of First Year Math Program) 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 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 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, 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

  • 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 MTH461 (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. 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


Applied and Computational Mathematics Option

With a core of computation-oriented courses, the applied and 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 applied and 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.

  • 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)
  • Technical elective (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’ll take 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


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.

You can find detailed info regarding the mathematics program at the site


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:


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

  • 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.


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