Mathematics BS / Mathematics MS

Major: Mathematics
Degree Awarded: Bachelor of Science (BS) and Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 226.0
Co-op Options: One Co-op (Five years)
Classification of Instructional Programs (CIP) code: 27.0101
Standard Occupational Classification (SOC) code:

About the Program

The accelerated BSMS program in mathematics is an exciting opportunity for highly motivated math students to take full advantage of the academic resources that Drexel University, as a research university with a graduate program, has to offer. Graduates from this program have a more in-depth, richer understanding of the concepts introduced in the undergraduate courses, as well as, more complex topics introduced at an advanced level.

The combined degree offers our graduates a competitive advantage over students who have only obtained an undergraduate degree, allowing them to stand out when they start their professional careers. In addition, the program is highly recommended for students who intend to apply to doctoral programs in mathematics as well as related areas (such as statistics, biostatistics, public health, graduate actuarial studies, mathematical finance). Many of our BSMS students have been accepted in some of the country’s most elite and competitive graduate mathematics programs.

Admission Requirements

Students may apply to the combined BS/MS Mathematics program when they have attained 90.0 credits. To gain entry into the Mathematics BS/MS program, it is necessary, though not sufficient, to satisfy the following conditions:

Complete two of the following: MATH 331, MATH 332, MATH 401 and MATH 402, with an average GPA of at least 3.75 total in the two or more of these courses taken.

Have an overall GPA of at least 3.5

Have a GPA of at least 3.8 in the mathematics major

Applicant should meet with their adviser to determine eligibility and to create a plan of study to be reviewed by the graduate advisor. The graduate committee will make the final decision. If accepted, the student must fill out the Accelerated Degree Program Application Form to obtain permission from all necessary approving parties.

Students with multiple majors may apply to the Accelerated Math degree program as long as one of their undergraduate majors is Mathematics; however, they will need to obtain signatures of the Mathematics department advisers for their BS/MS Accelerated degree paperwork, not advisers from their other major(s).

Degree Requirements

General Education Requirements
CIVC 101Introduction to Civic Engagement1.0
COM 230Techniques of Speaking3.0
COOP 101Career Management and Professional Development *1.0
ENGL 101Composition and Rhetoric I: Inquiry and Exploratory Research3.0
or ENGL 111 English Composition I
ENGL 102Composition and Rhetoric II: Advanced Research and Evidence-Based Writing3.0
or ENGL 112 English Composition II
ENGL 103Composition and Rhetoric III: Themes and Genres3.0
or ENGL 113 English Composition III
UNIV S101The Drexel Experience1.0
UNIV S201Looking Forward: Academics and Careers1.0
Computer Science sequence:9.0
Computer Science Principles
Introduction to Computer Science
Computer Programming I
Computer Programming II
Any Biology (BIO) course3.0-4.0
Any Chemistry (CHEM) course3.0-4.0
Any Physics (PHYS) course3.0-4.0
Humanities electives6.0
Social sciences electives15.0
International studies or studies in diversity electives6.0
Free electives40.0
Mathematics Requirements
MATH 121Calculus I **4.0
MATH 122Calculus II4.0
MATH 123Calculus III4.0
MATH 200Multivariate Calculus4.0
MATH 201Linear Algebra4.0
MATH 210Differential Equations4.0
MATH 220 [WI] Introduction to Mathematical Reasoning3.0
MATH 331Abstract Algebra I4.0
MATH 332Abstract Algebra II3.0
MATH 401Elements of Modern Analysis I3.0
MATH 402Elements of Modern Analysis II3.0
Math Major Electives40.0
Select a minimum of 40 credits from the following:
Math Competition Problem Solving Seminar
Mathematics of Investment and Credit
Differential Equations II
Numerical Analysis I
Numerical Analysis II
Introduction to Optimization Theory
Probability and Statistics I
Probability and Statistics II
Probability and Statistics III
Mathematical Applications of Symbolic Software
Mathematical Applications of Statistical Software
Techniques of Data Analysis
Actuarial Mathematics
Vector Calculus
Complex Variables
Partial Differential Equations
Linear Algebra II
Introduction to Topology
Mathematical Finance
Introduction to Graph Theory
Introduction to Monte Carlo Methods
Tensor Calculus
MS required courses
MATH 504Linear Algebra & Matrix Analysis3.0
MATH 505Principles of Analysis I3.0
MATH 506Principles of Analysis II3.0
MATH 533Abstract Algebra I3.0
MATH 630Complex Variables I3.0
MATH 633Real Variables I3.0
MS electives ***27.0
Select a minimum of 27 credits from the following:
Applied Mathematics I
Applied Mathematics II
Applied Mathematics III
Applied Probability and Statistics I
Applied Probability and Statistics II
Applied Probability and Statistics III
Numerical Analysis I
Numerical Analysis II
Numerical Analysis III
Computer Simulation I
Computer Simulation II
Topics in Computer Simulation
Mathematics for Data Science
Combinatorial Mathematics I
Combinatorial Mathematics II
Topics in Combinatorial Math
Abstract Algebra II
Topics in Abstract Algebra
Topology I
Topology II
Numerical Computing
Sci Comp & Visualization I
Sci Comp & Visualization II
Topics in Sci Comp & Visualiz
Financial Mathematics: Fixed Income Securities
Probability Theory I
Probability Theory II
Topics in Probability Theory
Stochastic Processes I
Stochastic Processes II
Topics in Stochastic Processes
Partial Differential Equations I
Partial Differential Equations II
Partial Differential Equations III
Ordinary Differential Equations I
Ordinary Differential Equations II
Ordinary Differential Equations III
Complex Variables II
Topics in Complex Variables
Real Variables II
Real Variables III
Functional Analysis
Harmonic Analysis
Operator Theory
Integral Equations I
Transform Theory I
Transform Theory II
Lie Groups and Lie Algebras I
Lie Groups and Lie Algebras II
Lie Groups/Algebras III
Methods of Optimization I
Methods of Optimization II
Methods of Optimization III
Calculus of Variations
Algebraic Combinatorics
Mathematical Neuroscience
Total Credits226.0-229.0

Co-op cycles may vary. Students are assigned a co-op cycle (fall/winter, spring/summer, summer-only) based on their co-op program (4-year, 5-year) and major. 

COOP 101 registration is determined by the co-op cycle assigned and may be scheduled in a different term. Select students may be eligible to take COOP 001 in place of COOP 101.


Math majors must pass MATH 121 with a grade of B or higher.


In some cases, course substitutions may be made with courses from other departments. Elective courses taken outside the department must receive prior departmental approval in order to be counted toward the degree.

Writing-Intensive Course Requirements

In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.

A "WI" next to a course in this catalog may indicate that this course can fulfill a writing-intensive requirement. For the most up-to-date list of writing-intensive courses being offered, students should check the Writing Intensive Course List at the University Writing Program. Students scheduling their courses can also conduct a search for courses with the attribute "WI" to bring up a list of all writing-intensive courses available that term.

Sample Plan of Study

4+1, 1 co-op (Accelerated program completed in 5 years)

Students complete undergraduate requirements in four years, then convert to graduate status in the fifth and final year.

First Year
CS 150 or 1643.0CIVC 1011.0CS 1723.0VACATION
ENGL 101 or 1113.0CS 1713.0ENGL 103 or 1133.0 
MATH 1214.0ENGL 102 or 1123.0MATH 1234.0 
UNIV S1011.0MATH 1224.0MATH 2004.0 
(UG) Any Biology (BIO) Course3.0-4.0(UG) Any Chemistry (CHEM) Course3.0(UG) Any Physics (PHYS) Course3.0 
 14-15 14 17 0
Second Year
COM 2303.0MATH 2104.0(UG) Free Elective3.0COOP 1011.0
MATH 2014.0(UG) International/Diversity Studies Elective*3.0(UG) Humanities Elective*3.0(UG) Free Electives9.0
MATH 2203.0(UG) Mathematics (MATH) Electives**7.0(UG) Mathematics (MATH) Electives**7.0(UG) Humanities Elective*4.0
(UG) International/Diversity Studies Elective*3.0(UG) Social Science Elective*3.0(UG) Social Science Elective*3.0(UG) Social Science Elective*3.0
(UG) Social Science Elective*3.0   
 16 17 16 17
Third Year
MATH 4013.0MATH 4023.0  
(UG) Free Electives6.0UNIV S2011.0  
(UG) Mathematics (MATH) Elective**4.0(UG) Free Electives6.0  
 (UG) Social Science Elective*3.0  
 17 16 0 0
Fourth Year
(UG) Free Electives6.0(UG) Free Electives6.0(UG) Free Electives6.0VACATION
(UG) Mathematics (MATH) Electives**7.0(UG) Mathematics (MATH) Electives**6.0(UG) Mathematics (MATH) Electives**6.0 
MATH 5043.0MATH 5063.0(GR) Graduate Mathematics (MATH) Electives6.0 
MATH 5053.0MATH 5333.0  
 19 18 18 0
Fifth Year
(GR) Graduate Mathematics (MATH) Electives9.0(GR) Graduate Mathematics (MATH) Electives9.0MATH 6303.0 
  MATH 6333.0 
  (GR) Graduate Mathematics (MATH) Elective3.0 
 9 9 9 
Total Credits 226-227

 See degree requirements.


Select from MATH 222 [WI] , MATH 235, MATH 250, MATH 285, MATH 300, MATH 301, MATH 305, MATH 311, MATH 312, MATH 316, MATH 318 [WI] , MATH 319, MATH 320, MATH 321, MATH 322, MATH 323, MATH 387, MATH 422, MATH 449, MATH 450, MATH 475, MATH 483, MATH 489. MATH special topics courses may be substituted for Mathematics Electives with departmental permission.

Mathematics Faculty

David M. Ambrose, PhD (Duke University) Associate Department Head, Mathematics. Professor. Applied analysis and computing for systems of nonlinear partial differential equations, especially free-surface problems in fluid dynamics.
Jason Aran, MS (Drexel University). Associate Teaching Professor.
Jonah D. Blasiak, PhD (University of California at Berkeley). Associate Professor. Algebraic combinatorics, representation theory, and complexity theory.
Yasmine Boolakee-Pant, MS (University of Freiburg). Instructor.
Robert P. Boyer, PhD (University of Pennsylvania). Professor. Functional analysis, C*-algebras and the theory of group.
Fernando Carreon, PhD (University of Texas at Austin). Teaching Professor.
Patrick Clarke, PhD (University of Miami). Associate Professor. Homological mirror symmetry, Landau-Ginzburg models, algebraic geometry, symplectic geometry.
Daryl Falco, MS (Drexel University). Associate Teaching Professor. Discrete mathematics and automata theory.
Raymond Favocci, MS (Drexel University). Associate Teaching Professor.
Darij Grinberg, PhD (Massachusetts Institute of Technology). Assistant Professor. Algebraic Combinatorics, Noncommutative Algebra, Symmetric Functions, Hopf Algebras, Enumerative Combinatorics, Invariant Theory
Pavel Grinfeld, PhD (Massachusetts Institute of Technology). Associate Professor. Intersection of physics, engineering, applied mathematics and computational science.
Anatolii Grinshpan, PhD (University of California at Berkeley). Associate Teaching Professor. Function theory and operator theory, harmonic analysis, matrix theory.
Yixin Guo, PhD (University of Pittsburgh). Associate Professor. Biomathematics, dynamical systems, ordinary and partial differential equations and math education.
R. Andrew Hicks, PhD (University of Pennsylvania). Professor. Geometry; optics; computer vision.
Pawel Hitczenko, PhD (Warsaw University). Professor. Probability theory and its applications to analysis, combinatorics, wavelets, and the analysis of algorithms.
Jeffrey LaComb, PhD (Duke University). Assistant Teaching Professor. Rare Event Simulation, Dynamical Systems, Numerical Analysis and Mathematical Biology
Georgi S. Medvedev, PhD (Boston University). Professor. Ordinary and partial differential equations, mathematical neuroscience.
Cecilia Mondaini, PhD (Federal University of Rio de Janeiro). Assistant Professor. Analysis of Partial Differential Equations, Fluid Dynamics, Stochastic Processes
Shari Moskow, PhD (Rutgers University) Department Head. Professor. Partial differential equations and numerical analysis, including homogenization theory, numerical methods for problems with rough coefficients, and inverse problems.
Oksana P. Odintsova, PhD (Omsk State University). Teaching Professor. Math education; geometrical modeling.
Dimitrios Papadopoulos, MS (Drexel University). Assistant Teaching Professor.
Joel Pereira, PhD (University of North Carolina). Assistant Teaching Professor. Commutative Algebra
Ronald K. Perline, PhD (University of California at Berkeley) Undergraduate Adviser. Associate Professor. Applied mathematics, numerical analysis, symbolic computation, differential geometry, mathematical physics.
Marci A. Perlstadt, PhD (University of California at Berkeley). Associate Professor. Applied mathematics, computed tomography, numerical analysis of function reconstruction, signal processing, combinatorics.
Adam C. Rickert, MS (Drexel University). Associate Teaching Professor.
Eric Schmutz, PhD (University of Pennsylvania). Professor. Probabilistic combinatorics, asymptotic enumeration.
Li Sheng, PhD (Rutgers University). Associate Professor. Discrete optimization, combinatorics, operations research, graph theory and its application in molecular biology, social sciences and communication networks, biostatistics.
Gideon Simpson, PhD (Columbia University). Associate Professor. Partial differential equations, scientific computing and applied mathematics.
Xiaoming Song, PhD (University of Kansas). Associate Professor. Stochastic Calculus, Large Deviation Theory, Theoretical Statistics, Data Network Modeling and Numerical Analysis.
Jeanne M. Steuber, MS (Boston University). Associate Teaching Professor.
Kenneth P. Swartz, PhD (Harvard University). Assistant Teaching Professor. Applied statistics, data analysis, calculus, discrete mathematics, biostatistics.
K. Shwetketu Virbhadra, PhD (Physical Research Laboratory). Instructor.
Richard D. White, MS (Penn State University). Assistant Teaching Professor.
Hugo J. Woerdeman, PhD (Vrije Universiteit, Amsterdam). Professor. Matrix and operator theory, systems theory, signal and image processing, and harmonic analysis.
J. Douglas Wright, PhD (Boston University) Associate Department Head. Professor. Partial differential equations, specifically nonlinear waves and their interactions.
Dennis G. Yang, PhD (Cornell University). Associate Teaching Professor. Dynamical systems, neurodynamics.
Thomas (Pok-Yin) Yu, PhD (Stanford University). Professor. Multiscale mathematics, wavelets, applied harmonic analysis, subdivision algorithms, nonlinear analysis, applied differential geometry and data analysis.
Matthew Ziemke, PhD (University of South Carolina). Assistant Teaching Professor. Functional Analysis, Operator Algebras, Semigroups, Mathematical Physics

Emeritus Faculty

Howard Anton, PhD (Polytechnic Institute of Brooklyn). Professor Emeritus.
Loren N. Argabright, PhD (University of Washington). Professor Emeritus. Functional analysis, wavelets, abstract harmonic analysis, the theory of group representations.
Robert C. Busby, PhD (University of Pennsylvania). Professor Emeritus. Functional analysis, C*-algebras and group representations, computer science.
Ewaugh Finney Fields, EdD (Temple University) Dean Emeritus. Professor Emeritus. Mathematics education, curriculum and instruction, minority engineering education.
William M.Y. Goh, PhD (Ohio State University). Associate Professor Emeritus. Number theory, approximation theory and special functions, combinatorics, asymptotic analysis.
Patricia Henry Russell, MS (Drexel University). Teaching Professor Emerita.
Bernard Kolman, PhD (University of Pennsylvania). Professor Emeritus. Lie algebras; theory, applications, and computational techniques; operations research.
Charles J. Mode, PhD (University of California at Davis). Professor Emeritus. Probability and statistics, biostatistics, epidemiology, mathematical demography, data analysis, computer-intensive methods.
Chris Rorres, PhD (Courant Institute, New York University). Professor Emeritus. Applied mathematics, scattering theory, mathematical modeling in biological sciences, solar-collection systems.
Justin R. Smith, PhD (Courant Institute, New York University). Professor Emeritus. Homotopy theory, operad theory, quantum mechanics, quantum computing.
Jet Wimp, PhD (University of Edinburgh). Professor Emeritus. Applied mathematics, special factors, approximation theory, numerical techniques, asymptotic analysis.
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