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.
Applied Mathematics and Statistics
Chairperson
Joseph Mitchell, Mathematics Building P-134A (631) 632-8366, joseph.mitchell@stonybrook.edu
Graduate Program Director
David Green, Mathematics Building P-137 (631) 632-9344, david.green@stonybrook.edu
Graduate Secretary
Christine Rota, Mathematics Building P-141 (631) 632-8360, christine.rota@stonybrook.edu
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
Web Site
http://www.ams.stonybrook.edu/
Application
https://graduateadmissions.stonybrook.edu/apply/
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.
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
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
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
Statistics
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.
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.
Distinguished Teaching Professor
Tucker, Alan, Ph.D., 1969, Stanford University: Graph theory; combinatorial algorithms.
Professor
Ahn, Hongshik, Graduate Program Director, 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
Uryasev, Stan, Endowed Chair of Quantitative Finance, Ph.D., 1983, Glushkov Institute of Cybernetics; quantitative finance, risk management, stochastic optimization
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; hierarchical mixture modeling.
Liu, Zhenhua, Ph.D., 2014, California Institute of Technology: Smart energy/sustainable Information Technology (IT) and IT for sustainability; big data platforms; optimization; algorithms.
Polak, Pawel, Ph.D., 2014, Swiss Finance Institute: computational statistics
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
Reuter, Matthew, Ph.D., 2011, Northwestern University: Computational chemistry, mathematical physics
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, Assistant Professor, Ph.D., 2002, Cornell University: theoretical biophysics.
Balazsi, Gabor, Associate Professor, Ph.D., 2001, University of Missouri: Synthetic gene circuits
Bender, Michael3, Professor, Ph.D., 1996, Harvard University, combinatorial algorithms.
Brinkman, Braden, Assistant Professor, Ph.D., 2013, University of Illinois at Urbana-Champaign, neuroscience.
Chen, Chao, Assistant Professor, Ph.D., Machine learning, Topological data analysis, Biomedical image analysis
Colosqui, Carlos, Associate Professor, Ph.D., 2009, Boston University: Microfluidics, Nano/Micro-Electromechanical Systems
Deasy, Joseph, Chair, Department of Medical Physics, Ph.D., 1992, University of Kentucky: Memorial Sloan Kettering Cancer Center: Medical physics, Statistical modeling, Machine learning, Cancer biology, Radiobiology
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, Leading Professor, Ph.D., 1975, Cornell University: Game theory; mathematical economics.
Elkin, Rena, Professor, Health Policy and Management, Ph.D., Harvard University, Columbia University: Cancer screening, treatment, and outcomes using population-based observational decision analysis
Gandhi, Anshul, Associate 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 Technology.
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, Research Associate Professor, Ph.D., 2006, University of Florida: Statistics.
Kim, Aaron, Associate Professor, Ph.D., 2005, Sogang University: Finance and Statistics.
Koo, Peter, Assistant Professor, Ph.D., 2015, Yale University, Quantitative biology
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.
Lin, Yuwei, Computational Scientist, Brookhaven National Lab, Ph.D., 2016, University of South Carolina: Computational science
Lindquist, Brent, Professor, Ph.D., 1981, University of Manitoba: 3D Image analysis; geostatistics and conditional simulation; front tracking.
Liu, Ji, Assistant Professor, Ph.D., 2013, Yale University: Distributed control and computation, multi-agent systems, social networks, epidemic networks, and power networks
Lynch, Heather, Professor, Ph.D., 2006, Harvard University: Development and application of statistics and mathematics to conservation biology
Mahdavi, Kazem, Research Professor at AMS, SUNY Korea, 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
Navlakha, Saket, Associate Professor, Ph.D, 2011, University of Maryland: Neural circuit computation
O, Suil, Ph.D., 2011, Assistant Professor at AMS, SUNY Korea, Extremal spectral graph theory.
Oh, Jung Hun, Associate Attending Computer Scientist, Memorial Sloan Kettering Cancer Center, Ph.D., University of Texas at Arlington: Bioinformatics, machine learning
Park, Memming, Associate 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, 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.
Robertazzi, Thomas, Professor, Ph.D., 1981, Princeton University: Scheduling, exascale computing, quantum computing, parallel processing, electric power
Rushton, Gregory, Professor, Ph.D., 2004, University of South Carolina: Conceptual change in tertiary chemistry learning environments
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.
Sharp, David4, Professor, Ph.D., 1963, California Institute of Technology: Mathematical physics; computational fluid dynamics.
Simmerling, Carlos, Professor, Ph.D., 1994, University of Illinois at Chicago: Computational structural biology
Skorin-Kapov, Jadranka, Professor, Ph.D., 2014, Stony Brook University, 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.
Tiano, Michael, Director of Business Deverlopment of Quantitative Strategies, ExodusPoint Capital Management, LP, Ph.D., 2017, Stony Brook University: Quantitative finance
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, Adjunct Professor, Ph.D., 1955, Columbia University.
Yang, Jie, Assistant Professor, Ph.D., 2006, University of Florida: Statistics.
Yin, Zhaozheng, Associate Professor, Ph.D., 2009, Pennsylvania State University: Biomedical image analysis, Computer vision, Machine learning, Cyber-physical systems, Human-robot collaboration
Zador, Anthony, Professor, Ph.D., 1994, Yale University: Neuroscience
Zhang, Peng, Professor, Ph.D., 2012, Stony Brook University, Department of Applied Mathematics and Statistics: Computational Applied Mathematics.
Zhang, Minghua, Distinguished Professor, Ph.D., 1987, Academia Sinica, China: Climate modelling, Atmospheric dynamics
Number of teaching assistant and research assistants, spring 2022: 117
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
Applied Mathematics and Statistics
Chairperson
Joseph Mitchell, Mathematics Building P-134A (631) 632-8366, joseph.mitchell@stonybrook.edu
Graduate Program Director
David Green, Mathematics Building P-137 (631) 632-9344, david.green@stonybrook.edu
Graduate Secretary
Christine Rota, Mathematics Building P-141 (631) 632-8360, christine.rota@stonybrook.edu
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
Web Site
http://www.ams.stonybrook.edu/
Application
https://graduateadmissions.stonybrook.edu/apply/