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Applied Mathematics and Statistics

  • Program Overview

    Applied Mathematics and Statistics Department

    The Department of Applied Mathematics and Statistics, within the College of Engineering and Applied Sciences, offers programs in computational applied mathematics, operations research, quantitative finance, statistics, and computational biology leading to the M.S. and Ph.D. degrees. The department offers an integrated series of courses and seminars, supervised reading, and facilities for research. Emphasis is on the study of real-world problems, computational modeling, and the development of necessary analytical concepts and theoretical tools. A state-of-the-art, computational laboratory is operated for student education and research, with access available to university­-based high-­performance computing facilities. It also features a network of advanced Unix workstations and modern printing facilities. The laboratory’s full-time staff is available to help students become familiar with the laboratory facilities.

    Students participate in joint research with 5 national laboratories, several industrial groups and various sciences, biomedical, and engineering programs. Students, who receive a broad training, find themselves excellently prepared for careers in government and industry in which mathematics is used as a computational or conceptual tool.

    Faculty research programs receive significant external funding and provide students with an opportunity for active participation in a variety of projects in all areas of the department. Faculty interests include applied graph theory, biostatistics and computational biology, structure-based drug design, computational fluid dynamics, combinatorial optimizations, computational statistics, data analysis, flow through porous media, fracture mechanics, inverse problems, mixed-boundary value problems, nonlinear conservation laws, quantitative finance, reliability theory, risk management, robust estimation, nonparametric statistics, stochastic modeling and sequential decision making and structure-­based drug design. Most doctoral students are supported through either a research or teaching assistantship.

    The Ph.D. program normally takes about four to five years for students with a strong analytical and computing background. The M.S. programs, when pursued on a full-time basis, may be completed in three or four semesters. Students who have taken graduate courses before enrolling at Stony Brook may request transfer of up to twelve credits. If such a request is approved, it may be possible to complete the M.S. degree in two semesters. It is strongly urged that all applicants develop some facility in computer programming.

    A more detailed description of the graduate program is available from the departmental office. This includes specific distribution requirements, fields of specialization, and information on the preliminary and qualifying examinations. Interested students should request information and application forms as early as possible, especially if they plan to apply for financial aid.

    Advanced Graduate Certificate Program in Operations Research
    This advanced certificate program of 18 credits, consisting of six three-credit courses, trains students in the fundamental mathematical tools for working in the operations research profession. Operations research is the field of applied mathematics related to efficient management of the activities of private companies, government agencies and nonprofit organizations. The following courses are required for certificate: AMS 507 Introduction to Probability, AMS 540 Linear Programming, AMS 550 Stochastic Models, AMS 553 Simulation and Modeling, AMS 572 Data Analysis I, plus one (3 credit) elective chosen by student in consultation with an advisor.

    Advanced Graduate Certificate Program in Quantitative Finance
    This advanced certificate program of 15 credits, consisting of five three-­credit courses, trains students in the fundamentals required for the application of quantitative methods in the financial world. The certificate is open to students in related graduate programs at Stony Brook, as well as to non­-matriculated students registered through the School of Professional Development. The following courses are required for certificate: AMS 511 Foundations of Quantitative Finance, AMS 512 Capital Markets & Portfolio Theory, AMS 513 Financial Derivatives & Stochastic Calculus, one elective chosen from AMS 514­523, plus one additional (3­-credit) elective chosen by the student with the approval of an advisor.

    Combined B.S./M.S. Degree

    Undergraduate applied mathematics majors, with strong academic credentials may apply for admission to the special Bachelor of Science-Master of Science program in Applied Mathematics and Statistics at the end of the junior year. The combined B.S./M.S. program in applied mathematics and statistics allows students with superior academic records to use up to six graduate credits toward the B.S. and M.S. requirements. In essence, those six credits count toward two goals simultaneously. Normally, it would take six years to complete two separate degrees, but with the combined B.S./M.S. program, there is only a 5 year commitment (10 semesters). The advantage of the combined program is that the M.S. degree can be earned in less time, thus costing less money than that required by the traditional course of study. A minimum cumulative GPA of 3.3 in all courses, as well as a GPA of 3.5 in required courses for the AMS major, is typically required to apply for the combined degree program; exceptions may be made for students with significantly improved

    Students apply to the program during their junior year. In the first semester of the senior year, students in the B.S./M.S. program are granted permission to take up to six graduate credits which will be applied towards the Masters degree requirements. In the second semester of the senior year, they become enrolled as graduate students. Because students in this program only need to earn 114 undergraduate credits, they are usually finished with undergraduate coursework by the first semester of their senior year. If needed, however, they may enroll in up to twelve credits of undergraduate coursework during the second semester of senior year. The undergraduate degree is issued at the end of the senior year, and the student continues in the graduate program through the fifth year. The requirements stated in the Graduate Bulletin must be earned to qualify the student for the master’s degree; this includes a total of at least 30 graduate level credits (including the six taken as an undergraduate). Further information about the combined program may be obtained from either the graduate program director or the undergraduate program director.

    Part-Time Graduate Studies
    In addition to the full-time graduate program leading to the M.S. and Ph.D. degrees, the department conducts a part-time program on campus. The part-time program is governed by regulations governing the resident full-time program with the exception that students in the part-time program have greater flexibility in choosing the time for the qualifying examination if they are contemplating pursuing the Ph.D.

    The purpose of the part-time program is to provide an opportunity for men and women who are employed full time to pursue graduate study leading to advanced degrees in applied mathematics, statistics, and operations research. Applicants who hold a bachelor’s degree in applied mathematics, mathematics, engineering, physical sciences, life sciences, or social sciences with a strong background in undergraduate mathematics will be considered for admission to this program. Qualified students may continue beyond the master’s degree for the Ph.D. degree.

    Additional information, including the scheduling of courses for part-time students, may be obtained from the graduate program director.

  • Admissions

    Admission Requirements of Applied Mathematics and Statistics Department

    For admission to graduate study, the minimum requirements are as follows:

    A. A bachelor’s degree in engineering, mathematics, the physical sciences, or in the life or social sciences with a strong mathematics background.

    B. A minimum overall grade point average of at least 3.00, as well as a minimum grade point average of 3.00 in all courses with a significant mathematical or quantitative component.

    C. Results of the Graduate Record Examination (GRE) General Test.

    D. Three letters of reference.

    E. Official transcripts for all undergraduate study completed.

    F. Acceptance by both the Department of Applied Mathematics and Statistics and the Graduate School.

    G. In some circumstances, a student may be admitted provisionally although they are missing some of the above requirements. Students admitted provisionally must follow an approved course sequence and maintain a cumulative GPA of at least 3.0 during the first year of graduate study before being admitted to full degree candidacy.

  • Degree Requirements

    Requirements for the M.S. Degree in Applied Mathematics and Statistics

    In addition to the minimum Graduate School requirements, the following are required:

    A. Course Requirements
    The M.S. degree in the Department of Applied Mathematics and Statistics requires the satisfactory completion of a minimum of 30 graduate credits in letter-graded (A, B, C, F) graduate courses, with some specializations requiring up to 36 credits.

    All credits in satisfaction of the degree must be at the graduate level. The department may impose additional requirements as described below. In addition, the cumulative grade point average for all courses taken must be B or higher, and at least 18 credits of all courses taken must carry a grade of B or above, and the grade point average over all core (non­ elective) requirements must be 3.0 or higher.

    The student pursues a program of study planned in consultation with an academic advisor. The program and any subsequent modifications require approval by the graduate program director.

    Core Requirements for the M.S. Degree

    1. Computational Applied Mathematics

    AMS 501 Differential Equations and Boundary Value Problems

    AMS 503 Applications of Complex Analysis

    AMS 510 Analytical Methods for Applied Mathematics and Statistics

    AMS 526 Numerical Analysis I

    AMS 527 Numerical Analysis II

    AMS 528 Numerical Analysis III

    AMS 595 Fundamentals of Computing (1 credit)

    Four elective courses (12 credits total) chosen in consulation with advisor

    2. Computational Biology

    AMS 507 Introduction to Probability

    AMS 510 Analytical Methods for Applied Mathematics and Statistics

    MCB 520 Graduate Biochemistry OR

    CHE 541 Biomolecular Structure and Analysis

    AMS 531 Laboratory Rotations in Computational Biology (two semesters, 0 credit)

    AMS 532 Journal Club in Computational Biology (two semesters, 0 credit)

    AMS 533 Numerical Methods and Algorithms in Computational Biology

    AMS 535 Intro to Computational Structural Biology & Drug Design

    AMS 537 Biological Networks & Dynamics

    AMS 539 Introduction to Physical & Quantitative Biology (0 credit)

    CSE 549 Computational Biology

    Three elective courses (9 credits total) chosen in consultation with advisor

    3. Operations Research

    AMS 510 Analytical Methods for Applied Mathematics and Statistics

    AMS 507 Introduction to Probability

    AMS 540 Linear Programming

    AMS 550 Stochastic Models

    AMS 553/CSE 529 Simulation and Modeling

    One course in statistics (AMS 570 - 586)

    AMS 595 Fundamentals of Computing (1 credit)

    Four elective courses (12 credits total) chosen from AMS 542­-556; one of these may be substituted by an additional statistics course (AMS 570-­586), and one may be substituted by a quantitative finance course (AMS 511­-523)

    4. Statistics

    AMS 510 Analytical Methods for Applied Mathematics and Statistics

    AMS 507 Introduction to Probability

    AMS 570 Mathematical Statistics I

    AMS 572 Exploratory Data Analysis

    AMS 573 Design & Analysis of Categorical Data

    AMS 578 Regression Theory

    AMS 582 Design of Experiments

    AMS 597 Statistical Computing

    Two elective courses (6 credits total) chosen in consultation with advisor

    5. Quantitative Finance

    AMS 507 Introduction to Probability

    AMS 510 Analytical Methods for Applied Mathematics and Statistics

    AMS 511 Foundations of Quantitative Finance

    AMS 512 Capital Markets & Portfolio Theory

    AMS 513 Financial Derivatives and Stochastic Calculus

    AMS 514 Computational Finance

    AMS 516 Statistical Methods in Finance

    AMS 517 Quantitative Risk Management

    AMS 518 Advanced Stochastic Models, Risk Assessment & Portfolio Optimization

    AMS 572 Data Analysis I

    FIN 539 Investment Analysis

    One elective course (3 credits total) chosen in consultation with advisor

    Elective Requirements for the M.S. Degree

    Unless otherwise specified, any graduate-level AMS or other graduate-level courses in a related discipline approved by the graduate program director may be used to satisfy the credit requirement beyond the core course requirement.

    B. Final Recommendation
    Upon the fulfillment of the above requirements, the faculty of the graduate program will recommend to the dean of the Graduate School that the Master of Science degree be conferred or will stipulate further requirements that the student must fulfill.

    C. Time Limit
    All requirements for the Master of Science degree must be completed within three years of the student’s first registration as a full-time graduate student.

    Requirements for the Ph.D. Degree in Applied Mathematics and Statistics

    A. Course Requirements
    The course of study prescribed for the M.S. degree provides basic guidelines for doctoral study. The student pursues a program of study planned in consultation with an academic advisor. The program and any subsequent modifications require approval of the graduate program director.

    B. Qualifying Examination
    A student must pass a two-part qualifying examination to be allowed to continue toward the Ph.D. degree. Each component of the qualifying examination is given twice a year at the beginning and the end of the Spring semester and is designed to test the student’s preparation to do research in applied mathematics. Each student must demonstrate competency in linear algebra and analysis and in-depth knowledge in one of the following areas:

    Computational Applied Mathematics

    Computational Biology

    Operations Research

    Quantitative Finance


    C. Research Advisor
    After completion of at least one year of full-time residence and prior to taking the preliminary examination, the student must select a research advisor who agrees to serve in that capacity.

    D. Preliminary Examination
    This is an oral examination administered by a committee and given to the student when he or she has developed a research plan for the dissertation. The plan should be acceptable to the student’s research advisor.

    E. Mathematical Writing Requirement
    The mathematical writing requirement is associated with the preliminary oral examination. The student must submit a document, typically 20 to25 double-spaced pages long, containing the research plan for the dissertation, including a well­referenced synopsis of the relevant background literature, as well as a summary of research work accomplished to date. It must be given to the members of the Preliminary Examination committee at least one week before the oral presentation.

    The document must be approved for satisfactory written style and use of technical English as well as for intellectual content; this will be assessed by the Preliminary Examination Committee, who is appointed by the graduate program director. International students may need extensive writing assistance from the ESL Tutoring Center established to provide exactly this kind of technical writing tutorial support.

    Tutorial assistance in writing, if needed, will also be provided to native students.

    F. Advancement to Candidacy
    After successfully completing all requirements for the degree other than the dissertation, the student is eligible to be recommended for advancement to candidacy. This status is conferred by the dean of the Graduate School upon recommendation from the graduate program director.

    G. Dissertation
    The most important requirement of the Ph.D. degree is the completion of a dissertation, which must be an original scholarly investigation. The dissertation must represent a significant contribution to the scientific literature and its quality must be comparable with the publication standards of appropriate and reputable scholarly journals.

    H. Dissertation Defense
    The student must defend the dissertation before an examining committee. On the basis of the recommendation of this committee, the Department of Applied Mathematics and Statistics will recommend acceptance or rejection of the dissertation to the dean of the Graduate School. All requirements for the degree will have been satisfied upon successful defense of the dissertation. There must be at least one year between advancing to candidacy and scheduling a dissertation defense.

    I. Minimum Residence
    At least two consecutive semesters of full-time study are required.

    J. Time Limit
    All requirements for the Ph.D. degree must be completed within seven years after the completion of 24 graduate credits in the program. The time limits for the qualifying and preliminary examinations and advancement to candidacy are described in the departmental Graduate Student Handbook.

    K. Teaching Requirement
    One academic year long teaching experience required.

  • Facilities
  • Faculty

    Faculty of Applied Mathematics and Statistics Department

    Distinguished Professor

    Feinberg, Eugene, Ph.D., 1979, Vilnius State University, Lithuania: Probability theory and statistics; control theory and applications in communication systems; transportation; computer networks and manufacturing.

    Glimm, James, Director, Institute for Multiscale Studies. Ph.D., 1959, Columbia University: Nonlinear equations, conservation laws; computational fluid dynamics; mathematical physics; quantitative finance.

    Mitchell, Joseph7, Chairman, Ph.D., 1986, Stanford University: Operations research; computational geometry; combinatorial optimization.

    Tannenbaum, Allen, Ph.D., 1976, Harvard University: Medical image analysis; computer vision; image processing; systems and control; controlled active vision; mathematical systems theory; bioinformatics; computer graphics.

    Tucker, Alan, Ph.D., 1969, Stanford University: Graph theory; combinatorial algorithms.

    Ahn, Hongshik, Ph.D., 1992, University of Wisconsin, Madison: Biostatistics; tree-structured regression

    Arkin, Esther5, Undergraduate Program Director, Ph.D., 1986, Stanford University: Combinatorial optimization; network flows; computational geometry.

    Chapman, Barbara, Ph.D., 1998, Queens University of Belfast: Computational Applied Mathematics

    Coutsias, Evangelos, Ph.D., 1979, California Institute of Technology: computational biology; methods for study of protein structure.

    Deng, Yuefan, Ph.D., 1989, Columbia University: molecular dynamics; parallel computing.

    Finch, Stephen, Ph.D., 1974, Princeton University: Robust estimation and nonparametric statistics.

    Harrison, Robert, Ph.D., 1984, University of Cambridge, theoretical and computational chemistry; high-performance computing; parallel programming; multi-resolution analysis; numerical methods.

    Li, Xiaolin, Ph.D., 1987, Columbia University: Computational fluid dynamics; numerical analysis.

    Rizzo, Robert, Ph.D., 2001, Yale University: Computational Biology, Structure-based  Drug Design.

    Samulyak, Roman, Ph.D, ,1999, New Jersey Institute of Technology; mathematical physics, computational applied mathematics

    Zhu, Wei, Ph.D., Deputy Chair, 1996, University of California, Los Angeles: Biostatistics;optimal experimental design; linear models; structural equation modeling.

    Associate Professors

    Green, David, Ph.D., 2002, MIT: Computational biology, protein structure.

    Hu, Jiaqiao, Ph.D., 2006, University of Maryland; stochastic optimization, dynamic programming.

    Jiao, Xiangmin, Ph.D., 2001, University of Illinois; numerical analysis, computational geometry.

    Kozakov, Dmytro, Ph.D., 2006, Boston College: Computational Biology

    MacCarthy, Thomas, Ph.D., 2005, University College London: Computational Immunology; Evolutionary Systems Biology.

    Xing, Haipeng, Ph.D. 2003, Stanford University: Statistical methods in finance, change-point detection.

    Wu, Song, Ph.D., 2008, University of Florida: Statistics

    Assistant Professors

    Kuan, Pei Fen, Ph.D., 2009 University of Wisconsin, Madison: Biostatistics; cancer genomics; hierarchial mixture modeling.

    Liu, Zhenhua, Ph.D., 2014, California Institute of Technology: Smart energy/sustainable Information Techology (IT) and IT for sustainability; big data platforms; optimization; algorithms.

    Reuter, Matthew, Ph.D., 2011, Northwestern University: Computational chemistry, mathematical physics

    Research Professors

    Frey, Robert, Ph.D., 1986, Stony Brook University: Quantitative finance

    Mullhaupt, Andrew, Ph.D. 1984, New York University: Quantitative finance.

    Research Assistant Professors

    Yu, Yan, Ph.D., 2005, Stony Brook University: Numerical analysis and computational fluid dynamics 

    Lim, Hyunkyung, Ph.D., 2009, Stony Brook University: Computational Applied Mathematics

    Affiliated Faculty

    Atwal, Gurinder, Assitant Professor, Ph.D., 2002, Cornell University: theoretical biophysics.

    Balazsi, Gabor, Associate Professor, Ph.D., 2001, University of Missouri: Synthetic gene circuits

    Bender, Michael3, Associate Professor, Ph.D., 1996, Harvard University, combinatorial algorithms.

    Colosqui, Carlos16, Assistant Professor, Ph.D., 2009, Boston University: Microfluidics, Nano/Micro-Electromechanical Systems

    Dill, Ken, Distinguished Professor, Ph.D., 1978, UC San Diego, Director, Laufer Center for Physical & Quantitative Biology; Computational modeling of proteins.

    Donaldson, Nora, Professor, Ph.D., 1988, University of Maryland: biostatistics.  

    Dubey, Pradeep1, Professor, Ph.D., 1975, Cornell University: Game theory; mathematical economics.

    Ferguson, David, Distinguished Service Professor, Ph.D., Department of Technology and Society at Stony Brook University; Quantitative reasoning, Technology in mathematics.

    Gandhi, Anshul, Assistant Professor, Ph.D., 2013, Carnegie Mellon University, Department of Computer Science at Stony Brook University; Performance modeling, queueing theory, Control theory.

    Gao, Yi, Assistant Professor, Ph.D., 2010, Georgia Institute of Techology.

    Grove, John4, Professor. Ph.D., 1984, Ohio State University: Conservation laws; front tracking.

    Gu, Xianfeng, Associate Professor, Ph.D., 2003, Harvard University, Department of Computer Science at Stony Brook University;  Computational conformal geometry.

    Held, Martin, Adjunct Associate Professor, Ph.D., Universitat Salzburg, Austria;  Computational geometry.

    Holod, Dmytro, Associate Dean & director of Graduate Studies, College of Business at Stony Brook University.

    Hou, Wei, Assistant Professor, Ph.D., 2006, University of Florida: Statistics.

    Kim, Aaron, Assistant Professor, Ph.D., Sogang University: Finance and Statistics.

    Kotov, Roman, Associate Professor, Ph.D., 2006, University of Iowa, Department of Psychiatry at Stony Brook University; Longitudinal research, Quantitative methods.

    Krasnitz, Alexander, Associate Professor, Ph.D., Cold Spring Harbor Laboratory.

    Levy, Sasha, Ph.D., Marsha Laufer Endowed Assistant Professor of Physical and Quantitative Biology, The Laufer Center and The Department of Biochemistry & Cell Biology, Stony Brook University; Quantitative biology.

    Lindquist, Brent, Professor, Ph.D., 1981, University of Manitoba: 3D Image analysis; geostatistics and conditional simulation; front tracking.

    Mahdavi, Kazem, Ph.D., 1983, SUNY Binghamton, Research Professor at AMS, SUNY Korea; Quantum computation, Geometrical group theory.

    Nadeem, Saad, Adjunct Assistant Professor, Ph.D., 2017, Stony Brook University: Computer Science

    Nemesure, Barbara, Associate Professor, Ph.D., 1993, SUNY @ Stony Brook: Statistical genetics.

    O, Suil, Ph.D., 2011, Assistant Professor at AMS, SUNY Korea; Extremal spectral graph theory.

    Park, Memming, Assistant Professor, Ph.D., Department of Neurobiology & Behavior at Stony Brook University; Biomedical engineering, Machine learning.

    Pinezich, John, Ph.D., Adjunct Professor, Ph.D.

    Powers, Scott13, Adjunct Professor, Ph.D., 1982, Columbia University: Genetic basis of cancer.

    Reinitz, John14, Ph.D., 1988, Yale University: Theory of fundamental biological processes; bioinformatics; optimization, developmental biology and gene regulation.

    Saltz, Joel, Professor, Ph.D., 1985, Duke University: biomedical engineering.

    Sandhu, Romeil, Assistant Professor, Ph.D., 2011, Stony Brook University, Department of Bioinformatics at Stony Brook University; Control based vision and learning.

    Schatz, Michael, Assistant Professor, Ph.D., 2010, University of Maryland: computational biology; genomics; genome assembly and validation; sequence alignment; statistical modeling; high performance and multicore computing; parallel algorithms; cloud computing.

    Sharp, David4, Professor. Ph.D., 1963, California Institute of Technology: Mathematical physics; computational fluid dynamics.

    Skorin-Kapov, Jadranka, Ph.D., 2014, Stony Brook University, Associate Professor, College of Business at Stony Brook University; Discrete optimization, Philosophy, Art history and criticism.

    Stoyanov, Stoyan, Ph.D., Research Professor, College of Business at Stony Brook University.

    Wang, Daifeng, Assistant Professor, Ph.D., Department of Biomedical Informatics at Stony Brook University, Bioinformatics.

    Wang, Jin9, Assistant Professor, Ph.D., 1991, University of Illinois: bio-molecular folding and recognition: protein - protein interactions.

    Wang, Xuefeng, Assistant Professor, Ph.D., 2012, Case Western Reserve University: epidemiology and biostatistics.

    Weinig, Sheldon, Associate Professor, Ph.D.

    Yang, Jie, Assistant Professor, Ph.D., 2006, University of Florida: Statistics.

    Yu, Jie, Associate Professor, Ph.D., 2000, MIT, School of Marine and Atmospheric Sciences at Stony Brook University; Ocean waves, Environmental fluid mechanics and coastal dynamics

    Zhao, Yue, Assistant Professor, Ph.D., 2011, UCLA, Department of Electrical and Computer Engineering at Stony Brook University; Smart grid, Renewable energy integration.


    Number of teaching assistant and research assistants, fall 2014: 90


    1) Department of Economics

    2) College of Business

    3) Department of Computer Science

    4) Los Alamos National Laboratory

    5) Recipient of the State University Chancellor’s Award for Excellence in Teaching, 2008

    6) Recipient of the State University Chancellor’s Award for Excellence in Teaching, 2002

    7) Recipient of the State University Chancellor’s Award for Excellence in Teaching, 1996

    8) Department of Technology and Society

    9) Department of Chemistry

    10) Department of Electrical and Computer Engineering

    11) Department of Preventive Medicine

    12) Advanced Acoustical Concepts

    13) Cold Spring Harbor Laboratory

    14) University of Chicago Statistics Department

  • Contact

    Applied Mathematics and Statistics

    Joseph Mitchell, Mathematics Building P-134A (631) 632-8366

    Graduate Program Director (PhD)
    Hongshik Ahn, Mathematics Building P-137 (631) 632-8372

    Graduate Program Director (MS, AGC)
    Wei Zhu , Mathematics Building P-138 (631) 632-8374

    Graduate Secretary
    Christine Rota, Mathematics Building P-141 (631) 632-8360

    Advanced Graduate Certificate Awarded
    Advanced Graduate Certificate in Operations Research; Advanced Graduate Certificate in Quantitative Finance

    Degrees Awarded
    M.S. in Applied Mathematics and Statistics; Ph.D. in Applied Mathematics and Statistics

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