Master of Science (Applied Mathematics)
The Master of Science in Applied Mathematics Program is designed for students seeking training in applied mathematics to pursue a career in the academe or in research and development in industry. Its curriculum is designed in such a way that graduates of this program are equipped with enhanced mathematical, analytical and critical thinking skills to solve complex problems in life and physical sciences, mathematical finance, etc. The program also provides the students with a solid mathematical foundation for doctoral studies in mathematics or related fields.
The program has four tracks:
 Mathematical Finance (MF)
 Mathematics in Life and Physical Sciences (MLPS)
 Numerical Analysis of Differential Equations (NADE)
 Optimization and Approximation (OA)
The MSAM program aims to provide and equip the students:
 the expertise in formulating and analyzing mathematical models. In particular, the application of mathematical methods to problems in life and physical science, finance, and other related disciplines.
 sufficient knowledge in the underlying mathematical theories in order to create new mathematical tools and models.
 training in the use of computational algorithms in solving mathematical problems arising from applications.
 the production of relevant and substantial research works in various fields of applied mathematics and their applications that would possibly lead to published works in peerreviewed scientific journals.

Admission into the Program
Applications for admission to the program are processed by the College of Science (more information here). Students can apply for admission during the 1st semester or 2nd semester.
Aside from the general requirements for admission set forth by the College of Science, applicants of the MSAM program must have a bachelor’s degree from a recognized institution of higher learning, and completion of Advanced Calculus and Linear Algebra courses, among others.
For more inquiries, please send an email to ddapr@math.upd.edu.ph.

Program Curriculum
A student may opt to take the thesis option or the nonthesis option. The maximum residence of any student under the MSAM program is five (5) years.
For the thesis option, students are required to take 24 units of formal graduate courses, 1unit graduate seminar, and 6 units of thesis. The thesis which will have to be defended before an Examination Committee. Submission of bound copies of the thesis will also be required.
For the nonthesis option, students are required to take 33 units of formal graduate courses, 1unit graduate seminar, a preliminary (written) examination, and a qualifying (oral) examination.

Mathematical Finance (MF)
The Mathematical Finance track of the MSAM program aims to:
 provide the mathematical concepts and techniques used in stochastic calculus and mathematical finance.
 provide basic knowledge on probability and statistics, economics, and the like for various problem solving skills in relation to finance and business applications.
 orient and train students in areas of optimal investment strategy and alternative finance.
 prepare a pool of skilled individuals equipped with the necessary knowledge in mathematical finance to pursue research or work in the industry.
Core courses include Math 211, Math 220.1 and Math 271. Track courses and electives include Math 265, Math 266, and any 3 additional courses of the ff: Math 250, Math 288, Stat 225, Stat 226, or other courses upon approval of the adviser. Refer to the table below for the curriculum checklist.
First Year
1st Semester 9 units 2nd Semester 9 units Math 211 3 Math 271.1 3 Math 220.1 3 Math 266 3 Math 265 3 Ellective (Allied Course) 3 Second Year
1st Semester 6 units 2nd Semester 4 units Elective (Allied Course) 3 Math 300 3 Elective (Allied Course) 3 Math 296 1 Third Year
1st Semester 3 units 2nd Semester Math 300 3 (for illustration purposes only)

Mathematics in Life and Physical Science (MLPS)
The Mathematics in Life and Physical Science track of the MSAM program aims to:
 introduce a variety of mathematical models on life and physical sciences.
 train the students to formulate mathematical models.
 equip the students with mathematical theory, techniques, and computational tools useful in the analysis and visualization of the dynamics of various mathematical models.
 provide students an overview of current approaches in this field.
 emphasize the close connection of models with real measurements depicting underlying mechanisms.
 prepare students how to identify parameters given experimental data and to validate models.
 engage the students in research projects arising from current priority areas.
Core courses include Math 211, Math 220.1 and Math 271. Track courses and electives include Math 235, Math 236, and any 3 additional courses of the ff: Math 221, Math 229, Math 250, Math 271.2, Math 288, or other courses upon approval of the adviser. Refer to the table below for the curriculum checklist.
First Year
1st Semester 9 units 2nd Semester 6 units Math 211 3 Math 235 3 Math 220.1 3 Elective (Allied Course) 3 Math 271.1 3 Second Year
1st Semester 9 units 2nd Semester 4 units Math 236 3 Math 300 3 Elective (Allied Course) 3 Math 296 1 Elective (Allied Course) 3 Third Year
1st Semester 3 units 2nd Semester Math 300 3 (for illustration purposes only)

Numerical Analysis of Differential Equations (NADE)
The Numerical Analysis of Differential Equations track of the MSAM program aims to:
 develop analytical skills in the study of existence, regularity and properties of solutions of differential equations (DEs) and their applications.
 equip students with mathematical methods in solving the existence and uniqueness of solutions of DEs.
 instill the importance of DEs in modeling physical phenomena.
 train students to use numerical algorithms in solving DEs.
 engage in fruitful research projects in the various applications of DEs.
Core courses include Math 211, Math 220.1 and Math 271. Track courses and electives include Math 221, Math 271.2, and any 3 additional courses of the ff: Math 222, Math 224, Math 229, Math 281, Math 288, or other courses upon approval of the adviser. Refer to the table below for the curriculum checklist.
First Year
1st Semester 9 units 2nd Semester 9 units Math 211 3 Math 221 3 Math 220.1 3 Math 271.2 3 Math 271.1 3 Ellective (Allied Course) 3 Second Year
1st Semester 6 units 2nd Semester 4 units Elective (Allied Course) 3 Math 300 3 Elective (Allied Course) 3 Math 296 1 Third Year
1st Semester 3 units 2nd Semester Math 300 3 (for illustration purposes only)

Optimization and Approximation (OA)
The Optimization and Approximation track of the MSAM program aims to:
 provide strong foundations in approximation theory and optimization.
 equip students with techniques in approximation theory and apply them to estimate various mathematical quantities.
 train students to formulate models of reallife problems, apply the relevant optimization algorithms and analyze the obtained solutions.
 expose the students to the current trends of research in other areas related to optimization and approximation.
 engage in quality research projects in the various applications of optimization and approximation.
Core courses include Math 211, Math 220.1 and Math 271. Track courses and electives include Math 222, Math 280, and any 3 additional courses of the ff: Math 221, Math 250, Math 271.2, Math 281, Math 288, or other courses upon approval of the adviser. Refer to the table below for the curriculum checklist.
First Year
1st Semester 9 units 2nd Semester 9 units Math 211 3 Math 271.1 3 Math 220.1 3 Math 222 3 Math 280 3 Ellective (Allied Course) 3 Second Year
1st Semester 6 units 2nd Semester 4 units Elective (Allied Course) 3 Math 300 3 Elective (Allied Course) 3 Math 296 1 Third Year
1st Semester 3 units 2nd Semester Math 300 3 (for illustration purposes only)

Registration Matters
Registration Process
Refer to the Graduate Student Guide from the UPD College of Science website.
Program Advisers
For students admitted to the MSAM program, please contact your program advisers listed below for your registration concerns.
Track Program Advisers Mathematical Finance (MF) Daryl Allen Saddi (dasaddi@math.upd.edu.ph) Mathematics in Life and Physical Science (MLPS)
Numerical Analysis of Differential Equations (NADE)Rhudaina Mohammad (rmohammad@math.upd.edu.ph) Optimization and Approximation (OA) Marrick Neri (marrick@math.upd.edu.ph)
Gino Angelo Velasco (gamvelasco@math.upd.edu.ph)