Skip to Navigation
    Johns Hopkins University - Whiting School of Engineering
   
 
  Nov 23, 2009
 
 
    
Skip Navigation

Applied and Computational Mathematics


Applied and computational mathematics is concerned with the use of mathematics to solve problems in diverse areas such as engineering, business, science, health care, information technology, and public policy. There is a strong connection between applied mathematics and modern computational methods, especially in the design and computer implementation of mathematical algorithms.

The Applied and Computational Mathematics (ACM) program prepares students for work in their areas of interest through instruction in mathematical and computational techniques of fundamental importance and practical relevance. The program allows students to choose an area of concentration such as probability and statistics, applied analysis, operations research, information technology and computation, or simulation and modeling. Students are also free to select courses from different areas to meet their individual needs. All students in the program will take a blend of introductory and advanced courses. Modern computing facilities are available for student use at the Kossiakoff Center of the Applied Physics Laboratory, the Montgomery County Campus, and the Homewood campus.

Program Committee

James C. Spall, Program Chair
Principal Professional Staff
Applied Physics Laboratory

Beryl Castello
Lecturer, Applied Mathematics and Statistics
Whiting School of Engineering

Stacy D. Hill
Senior Professional Staff
Applied Physics Laboratory

George Nakos
Professor, Mathematics
U.S. Naval Academy

Edward R. Scheinerman
Professor, Applied Mathematics and Statistics, and Vice Dean for Education 
Whiting School of Engineering

J. Miller Whisnant
Principal Professional Staff
Applied Physics Laboratory

Admission Requirements


M.S. Degree or Special Student.


Applicants must meet the general requirements for admission to graduate study, outlined in this catalog in the Admission Requirements section. The applicant’s prior education must include at least one mathematics course beyond multivariate calculus (such as advanced calculus, differential equations, or linear algebra). All applicants must be familiar with at least one programming language (e.g., C, C++, FORTRAN, or MATLAB).

Advanced Certificate for Post-Master’s Study.


Applicants must meet the criteria above and hold at least a master’s degree in applied and computational mathematics or a closely related area.

Course Requirements


M.S. Degree.


Ten one-term courses must be completed within five years. The 10 courses must include 625.403 (Statistical Methods and Data Analysis); at least one of 625.401 (Real Analysis) or 625.409 (Matrix Theory); and at least one of the two-term sequences 625.717-718 (Advanced Differential Equations: Partial and Nonlinear Differential Equations), 625.721-722 (Probability and Stochastic Processes I and II) or 625.725-726 (Theory of Statistics I, II). The remaining six courses must include at least four from the ACM program (courses numbered 625. XXX), with at least two of the four courses at the 700-level. Students are required to take at least one 700-level course outside of the sequences 625.717-718, 625.721-722, and 625.725-726. A student who has taken at least one year of undergraduate statistics or one semester of graduate statistics (outside of ACM) may substitute another 625.XXX course for 625.403 with approval of the student’s adviser. Two one-term elective courses are also to be taken. These may be from the ACM program or from another graduate program described in the catalog, subject to the approval of the student’s adviser. If chosen from another program, the courses are required to have significant mathematical content. A thesis or knowledge of a foreign language is not required.

Advanced Certificate for Post Master’s Study.


Six one-term courses must be completed within three years. At least four of the six courses must be ACM courses numbered 625.480 or higher, with at least three of these courses being at the 700-level. Courses 625.401 (Real Analysis), 625.403 (Statistical Methods and Data Analysis), and 625.409 (Matrix Theory) may not be counted toward the post-master’s certificate. At least one of the 700-level courses must be outside of the sequences 625.717-718, 625.721-722, and 625.725-726. Students are allowed to take one mathematically oriented elective course from outside the ACM program as part of the six courses for the certificate, subject to adviser approval.

A student with a long-run interest in pursuing a Ph.D. through the Applied Mathematics and Statistics (AMS) Department at the Homewood campus should coordinate his/her course plan with an ACM adviser and with a representative in the AMS Department. Certain courses within ACM may be especially helpful in passing the required entrance examination for the Ph.D. program. No priority of admission for the Ph.D. degree program is given to graduates of the ACM program.

Listed below are five concentration areas within Applied and Computational Mathematics. Students are free to focus their course selections in one of these areas. There is no requirement that a concentration area be chosen.

Course Descriptions


Courses numbered 700-level and above are open only to students who have been approved for graduate status. Courses are taught mainly at the Applied Physics Laboratory campus, but some courses are also offered at the Dorsey Center and Montgomery County campuses. For continuity, both semesters of a two-semester course should normally be taken at the same campus. Please refer to the Course Schedule published each term for exact dates, times, locations, fees, and instructors.

Non-Graduate Credit Courses


The 200-level courses offered are intended to provide mathematical background for graduate course work in EPP. These 200-level courses are not for graduate credit. Some students may find one or more of these courses useful as a refresher or to fill gaps in their training.

Non-Graduate Course Characteristics and Relationships


These non-graduate courses have the following characteristics and relationship to each other:

  • 625.201 is a broad review of calculus, linear algebra, and ordinary differential equations;
  • 625.250 is a deeper review of multivariate calculus and linear algebra, including complex variables, but the course does not cover differential equations;
  • 625.251 covers ordinary and partial differential equations and is especially oriented to providing the mathematics background for the Applied Physics Program and some tracks in the Electrical and Computer Engineering Program; and
  • 625.260 on linear systems is designed primarily for students entering the Electrical and Computer Engineering program, but may also be relevant to those in other programs with an interest in the theory, transforms, and algorithms associated with linear differential equations.