Mathematics BS / Mathematics MS

Major: Mathematics
Degree Awarded: Bachelor of Science (BS) and Master of Science (MS)
Calendar Type: Quarter
Total Credit Hours: 226.0
Co-op Options: Two Co-ops (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 Math program when they have attained between 90-130 credits. To gain entry into the Math dual degree 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 Development1.0
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
Discrete Event Simulation
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

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

BS-MS 5COP/2 co-ops

First Year
CS 150 or 1643.0CIVC 1011.0COOP 1011.0VACATION
ENGL 101 or 1113.0CS 1713.0CS 1723.0 
MATH 1214.0ENGL 102 or 1123.0ENGL 103 or 1133.0 
UNIV S1011.0MATH 1224.0MATH 1234.0 
(UG) Any Biology (BIO) course3.0-4.0(UG) Any Physics (PHYS) course3.0-4.0MATH 2004.0 
 (UG) Social Science elective*3.0(UG) Any Chemistry (CHEM) course3.0-4.0 
 14-15 17-18 18-19 0
Second Year
MATH 2014.0(UG) Mathematics (MATH) electives**10.0  
MATH 2203.0(UG) Free elective4.0  
(UG) Mathematics (MATH) elective**4.0   
(UG) Social Science Elective*3.0   
(UG) Free elective3.0   
 20 18 0 0
Third Year
(UG) Mathematics (MATH) electives**7.0UNIV S2011.0  
(UG) International Studies or Studies in Diversity elective*3.0(UG) Mathematics (MATH) electives**7.0  
(UG) Free elective4.0(UG) Free electives7.0  
 18 18 0 0
Fourth Year
MATH 4013.0MATH 4023.0(UG) Mathematics (MATH) elective**4.0(UG) International Studies or Studies in Diversity elective3.0
(UG) Mathematics (MATH) electives**8.0(UG) Humanities elective*3.0(UG) Social Science electives*3.0(UG) Social Science electives*6.0
(UG) Free elective3.0(UG) Free electives7.0(UG) Free electives6.0(UG) Free electives6.0
MATH 5043.0MATH 5333.0(GR) Graduate Mathematics (MATH) electives6.0(UG) Humanities elective*3.0
MATH 5053.0MATH 5063.0  
 20 19 19 18
Fifth Year
Graduate Mathematics (MATH) electives9.0Graduate Mathematics (MATH) electives9.0MATH 6303.0 
  MATH 6333.0 
  Graduate Mathematics (MATH) elective3.0 
 9 9 9 
Total Credits 226-229

Mathematics Faculty

David M. Ambrose, PhD (Duke University) Associate Department Head, Mathematics. Associate Professor. Applied analysis and computing for systems of nonlinear partial differential equations, especially free-surface problems in fluid dynamics.
Jason Aran, MS (Drexel University). Assistant Teaching Professor.
Jonah D. Blasiak, PhD (University of California at Berkeley). Associate Professor. Algebraic combinatorics, representation theory, and complexity theory.
Robert P. Boyer, PhD (University of Pennsylvania) Associate Head of the Mathematics Department. Professor. Functional analysis, C*-algebras and the theory of group representations.
Patrick Clarke, PhD (University of Miami). Assistant Professor. Homological mirror symmetry, Landau-Ginzburg models, algebraic geometry, symplectic geometry.
Daryl Falco, MS (Drexel University). Assistant Teaching Professor. Discrete mathematics and automata theory.
Raymond Favocci, MS (Drexel University). Assistant Teaching Professor.
Carlo Fazioli, PhD ( University of Illinois at Chicago). Assistant Teaching Professor. Computational Fluid Dynamics, Free Boundary Problems.
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). Assistant 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.
Robert Immordino, MS (Drexel University). Assistant Teaching Professor.
Ryan Kaliszewski, PhD (The University of North Carolina at Chapel Hill). Visiting Assistant Professor. Algebraic Combinatorics and Algebraic Geometry--specifically positivity results for generating polynomials.
Dmitry Kaliuzhnyi-Verbovetskyi, PhD (Kharkov University). Associate Professor. Operator theory, systems theory, complex analysis, C*-algebras and harmonic analysis.
Hwan Yong Lee, PhD (University of Utah). Assistant Teaching Professor. Electromagnetic wave propagation in composite media, optimization and inverse problem.
Georgi S. Medvedev, PhD (Boston University). Associate Professor. Ordinary and partial differential equations, mathematical neuroscience.
Taoufik Meklachi, PhD (University of Houston). Visiting Assistant Professor. Inverse Problems
Jennifer Morse, PhD (University of California, San Diego) Undergraduate Advisor. Professor. Algebraic combinatorics.
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.
Marna A. Mozeff, MS (Drexel University). Associate Teaching Professor. Working with Freshmen
Oksana P. Odintsova, PhD (Omsk State University). Associate Teaching Professor. Math education; geometrical modeling.
Dimitrios Papadopoulos, MS (Drexel University). Instructor.
Ronald K. Perline, PhD (University of California at Berkeley). 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). Assistant Professor. Partial differential equations, scientific computing and applied mathematics.
Justin R. Smith, PhD (Courant Institute, New York University). Professor. Homotopy theory, operad theory, quantum mechanics, quantum computing.
Xiaoming Song, PhD (University of Kansas). Assistant Professor. Stochastic Calculus, Large Deviation Theory, Theoretical Statistics, Data Network Modeling and Numerical Analysis.
Jeanne M. Steuber, MS (Boston University). Assistant Teaching Professor.
Kenneth P. Swartz, PhD (Harvard University). Assistant Teaching Professor. Applied statistics, data analysis, calculus, discrete mathematics, biostatistics.
Vaishalee T. Wadke, MS (Columbia University). 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) Graduate Advisor. Associate Professor. Partial differential equations, specifically nonlinear waves and their interactions.
Dennis G. Yang, PhD (Cornell University). Assistant 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.

Emeritus Faculty

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.
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.
Jet Wimp, PhD (University of Edinburgh). Professor Emeritus. Applied mathematics, special factors, approximation theory, numerical techniques, asymptotic analysis.
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