**Master of Science in Applied Mathematics**

**Application for Admission **

Application for the next fall admission should be submitted online in the time window from October 1^{st} of this year to March 1 of the next year. To apply, go to the Graduate Division MyGap .

The MS Applied Mathematics Program does not require additional supplemental materials besides Item 22 (Statement of Purpose) at end of your online application. The program admission does not require recommendation letters, resume, and personal statement. The Department of Mathematics and Statistics has limited TA positions. An application needs to be filed separately and reference letters are needed for the TA application.

**Program Advisor**

Please read the information below about the program. For further questions, please contact the Program Advisor Dr. Sam Shen, sam.shen@sdsu.edu.

**Program Overview**

The SDSU program of Master of Science in Applied Mathematics (Major Code: 17031, SIMS Code: 776314) provides excellent course work and research opportunities in modern applied mathematics with emphasis on computing, mathematical modeling, real-world applications, blended skills of mathematics-statistics-numerics, and cutting edge research topics, such as big data and cloud computing. The program prepares students for a wide range of career options that put mathematics to work. The career options include (a) technical or research positions with governmental laboratories and companies (e.g., U.S. Navy, SAIC, Apple, Google, Qualcomm, data analytics for various biotech companies, financial and security corporations), (b) teaching jobs at community colleges and universities, and (c) Ph.D. studies for further research in applied mathematics or related areas. The program has particular strength in computing, climate mathematics and bio-mathematics.

Graduates with skills in advanced applied mathematics, statistics, computer programing, and technical writing can receive excellent and highly paid job offers. A student entered ExoAnalytic Solutions, Inc. as an Algorithm Engineer in 2013 and received a promotion within six months. Another student received a $90K per year job offer six months before the completion of his degree. Still another student works on fraud detection using big data and cloud computing technologies and holds a job earning $130K per year plus bonus. Students are also doing well in Ph.D. studies after their applied mathematics M.Sc. degree. A student received a top campus wide fellowship from Notre Dame University and has written two papers from this M.Sc. thesis and four papers from his Ph.D. dissertation. The teaching option is also attractive. San Diego has many community colleges, such as City College, Miramar College, and Grossmont College. A recent graduate has a very successful career at City College.

The program has a characteristic of high flexibility, under which a student’s career goal can be supported effectively and optimally.

**Admission Requirements **

An applicant should typically satisfy the following requirements:

- An overall undergraduate GPA of 2.85 or better for the last 60 units, or equivalently the last two years of full time study.
- GRE General is required, but there is no specific score requirement. The GRE verbal, quantitative and writing scores will be evaluated together with an applicant’s overall qualifications.
- A bachelor’s degree in mathematics, applied mathematics, statistics, computer science, physics, geoscience, biology, engineering, economics, or a related field that makes intensive use of mathematics is recommended. Students from other undergraduate majors can be accepted but will need to make up the missing prerequisites while enrolled in the program.
- For international students, TOEFL is required. The paper-based TOEFL (PBT) score should be at least 550. The Internet-based TOEFL (IBT) should be at least 80. IELTS 6.5 can be used to replace TOEFL 80 to satisfy the language proficiency requirement. The minimum GPA for international students is 3.0 (B grade or 80%) in the last two years of full time studies.

To prepare for this degree program, it is expected that a student has acquired the knowledge of the following course material (SDSU course number in the round brackets) and the related skills:

- Linear Algebra (MATH 524) 1 semester
- Advanced Calculus (MATH 534 A&B) 2 semesters
- Numerical Analysis (MATH 541) 1 semester
- Probability and/or Statistics (STAT 550 and/or STAT 551A) 1 semester
- Computer programming proficiency on some platform, such as MATLAB, R, Java, and C++

Plus one or several more specialized courses:

- Differential Equations (MATH 537 and MATH 531)
- Numerical Analysis to Differential Equations (MATH 542)
- Introduction to Mathematical Modeling (MATH 336)
- Optimization Theory (MATH 562)
- Mathematical Statistics (STAT 55lB);
- Complex Analysis (MATH 532);
- Abstract Algebra (MATH 521A);
- Plus an application field: Biology, Geoscience, Physics, Computer Science, Engineering, Economics, etc.

Deficiencies may be remediated by taking appropriate courses during the graduate studies. These deficiencies should be completed within the first year unless scheduling difficulties make this impossible.

Other general admission requirements and information can be found from the following links.

- Graduate admissions information from the Mathematics and Statistics Department
- Graduate admissions information from SDSU Graduate Bulletin.
- Graduate application NOT for international students.
- Graduate application for international student.
- SDSU Test Office (GRE)

**Financial Support**

The department offers financial support through Graduate Teaching Assistantships and Graduate Research Assistantships: see application.

**Official Program of Study**

Students should assemble a specific program of study in consultation with the program advisor or thesis research advisor to make sure that their coursework and thesis research are appropriately aimed at the their specific career objectives. To assist with advising, a student should submit to the program advisor a short description (100-200 words) about his or her particular interests and expectations from the program. Based on this description, the program advisor will contact an appropriate faculty member to help design the student’s program. A student is advised to select a faculty member as his/her thesis research advisor as soon as possible, certainly no later than the end of his/her first year of study.

An Official Program of Study form should be filled out in consultation with the graduate advisor and submitted to the Graduate Division as early as possible but no later than the semester prior to anticipated graduation. We advise students filing the Official Program of Study during the first year of their study.

**Degree Course Requirements**

M.Sc. Candidates must take 30 units of advisor approved upper division and graduate courses. All programs must include at least 21 units from the Department of Mathematics and Statistics and at least 15 units selected from 600- and 700-level courses. At most, six units in MATH 797 (Research), MATH 798 (Special Study), or MATH 799A (Thesis or Project) will be accepted for credit toward the degree. Up to 9 units of 500-level courses may be counted toward the course requirements.

Most students are encouraged to take the core courses in Applied Mathematics: Mathematical Modeling (MATH 636), Optimization Theory (MATH 662), Numerical Analysis (MATH 542), and Mathematical Statistics (STAT 551B).

By the end of the first year, the student should select a faculty member as thesis advisor and a Masters thesis research topic. The thesis requires about two courses worth of effort and most students enroll in MATH 797 (Research) for the research portion prior to writing and defending the thesis (MATH 799A). The student may be asked to enroll in a Technical Writing course or to show other evidence of proficiency in technical writing if the advisor feels that this course is desirable. If the thesis writing cannot be completed within the semester planned, a candidate can register for MATH 799B (THESIS EXTENSION).

**Program Faculty **

Peter Blomgren– Numerical analysis, image processing.

Ricardo Carretero –Mathematical physics, nonlinear dynamics.

Jose Castillo – Numerical analysis, computational fluid dynamics.

Chris Curtis– Nonlinear waves, asymptotic methods, numerical methods.

Jerome Gilles– Applied harmonic analysis, data-driven methods for signal and image analysis, wavelets.

Stefen Hui– Signal analysis and communication applications.

Joseph Mahaffy – Modeling, biomathematics, time-delay differential equations.

Antonio Palacios — Nonlinear dynamical systems, mathematical physics.

Peter Salamon – Modeling, optimization, thermodynamics, mathematical biology, SDSU Area of Excellence in Viral Information.

Toni Luque Santolaria －Biomathematics, numerical methods, SDSU Area of Excellence in Viral Information.

Bo-Wen Shen– Climate modeling, scientific computing, SDSU Area of Excellence in Climate and Sustainability Studies

Sam Shen – Program Advisor; Climate data analysis, climate modeling, nonlinear waves, SDSU Area of Excellence in Climate and Sustainability Studies

Students have opportunities to take courses in mathematics, statistics, or computational sciences from research active faculty members. A wide array of research topics are available to students, ranging from traditional differential equation oriented mathematical modeling and statistical data analysis, to modern stochastic modeling and big data science. The application fields range from biology, climatology, civil and electrical engineering, to ocean waves, signal analysis and theoretical physics. The program faculty have strong collaborative relationships with various businesses and national labs, such as NASA Jet Propulsion Laboratory at Pasadena and NAVY Space and Naval Warfare Systems Center Pacific at San Diego. The faculty have intensive research activities funded by numerous governmental agencies and businesses, including National Science Foundation, National Institute of Health, NASA, Department of Energy, National Oceanic and Atmospheric Administration, and California State University system. Students in the program have internship or research opportunities with the funded projects or collaborative labs or businesses.

For questions, please write to the program advisor: Dr. Sam Shen, sam.shen@sdsu.edu

rev: 02/05/15