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Graduate Catalog

Department of Computational Science

(585) 395-2021

Chair/Professor: Osman Yasar, PhD, University of Wisconsin/Madison; Assistant Professors: Leigh J. Little, PhD, University of Arizona; Robert E. Tuzun, PhD, University of Illinois-Urbana/Champaign.

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Computational science is a new field, offering a combined education in mathematics, computer science, and applications of science, engineering and business. Students benefit from a program that enhances an academic area of interest with additional tools from computer science and mathematics. We are in the middle of an information revolution that enhances our ability to learn and specialize in more than one field. Today's careers demand multiple skills and even degrees. Finding an economical way to prepare for this multifaceted high technology market is the key to new generations.

Computer modeling enables us to study systems before they are put into production, saving us billions of dollars. Nearly all areas of science and engineering now use computers for modeling and problem solving. The aerospace industry uses this approach to design safe and economical aircraft. The automobile industry uses similar techniques to design better engines and safe vehicles. Computational technology is used in the medical and pharmaceutical industries to develop new drugs, process medical records, and assist in medical procedures. Meteorologists use computational techniques to predict the weather and long-term climate changes. Ecologists and biologists use computer models to study the environment, population dynamics, and the influence of pollutants on the body, the air, and the ocean. The genetic blueprint of human beings is about to be mapped out in its entirety through computer modeling. Cognitive scientists model brain function using the methods of computational science. Economists use computers to predict behavior of many financial systems, including the stock market.

Computers are everywhere, not only in industrial labs, workplaces, and home offices, but also in our appliances and cars, helping us with almost every aspect of our lives. The next phase of the information revolution will involve smart devices and hand-held computers. Wireless technology will connect billions of such devices, making the use of computers as essential as the telephone today. To be part of a growing information technology market, a combined education of computer science and application sciences is the right investment. Students with a wide interest in computers and other sciences will now be able to pursue a rich and diverse education at SUNY Brockport under one single program.

The program's flexibility allows students to apply math, computer and computational skills to an area of their choice. Scholarships and graduate assistantships may be available for highly qualified candidates. Graduates are well prepared for future employment in industry, research, and academia. The incredible growth in the information-technology sector promises many exciting opportunities for those with computational expertise, including teaching in our public schools. The department has received equipment support from the Intel Corporation as well as the Silicon Graphics, Inc. The department works very closely with local area industry, particularly Xerox Corporation and Eastman Kodak Company. Our recent graduates have found employment at such agencies as Lockheed Martin, Xerox, Paychex, General Electric, Rochester Computer Systems, United States Navy, and the Rochester City School District.

Graduate Degree in Computational Science
The Master of Science (MS) requires 35 credits of graduate courses. This includes 12 credits of elective courses and 23 credits of required courses. The program is open to students with a BS in many fields, including computer science, math, physics, chemistry, biology, earth sciences, engineering, business, and visual arts.

(a) Required Courses (23 credits):
Credits
  MTH 581 Discrete Mathematics
3
  CSC 506 Advanced Data Structures
4
  CPS 533 Scientific Visualization
3
  CPS 602 Advanced Software Tools
3
  CPS 644 Supercomputing and Applications
3
  CPS 698 Graduate Seminar
1
  CPS 699 Independent Study
3
  CPS 700 Project Paper
3
   
(b)

Elective (Application) Courses (12 credits)
(500 and higher-level courses)

Areas of Concentration (Applications):
Computational Biology
Computational Chemistry
Computational Economics
Computational Engineering
Computational Finance
Computational Mathematics
Computational Physics
Computational Sociology
Recommended Electives: *

12
  CPS 504 Applied and Computational Mathematics
3
  CSC 511 Computer Architecture
3
  CPS 517 Introduction to Computational Chemistry
3
  CSP 521 Introduction to Computational Physics
3
  CSP 541 Introduction to Computational Finance
3
 

CSP 555 Introduction to Computational Fluid Dynamics

3
  CSP 561 Introduction to Computational Biology
3
  CPS 604 Computational Methods in Physical Sciences
3
  CPS 632 Deterministic Dynamical Systems
3
  CPS 633 Stochastic Dynamical Systems
3
 

CSC 529 Object-oriented Programming

3
  CSC 519 Computer Networks
3
  CSC 522 Relational Database Design
3
  CSC 511 Computer Architecture
3
  CSC 512 Operating Systems
3
  CSC 583 Theory of Computation
3
  CSC 601 Programming Languages
3
  MTH 571 Numerical Analysis
3
  MTH 555 Differential Equations
3
  MTH 542 Statistical Methods
3
  MTH 562 Math Models for Decision Making
3
   
  TOTAL Credits (including electives)
34

*Please consult with faculty advisor about availability of additional electives.

Graduate Admission
Admission into the MS in Computational Science program is competitive and is based upon previous academic performance, letters of recommendation, and work experience. International students must score at least 550 on the written TOEFL test. Applicants must have a 3.0 GPA, yet a conditional admission may be granted in unusual cases. Application materials to be submitted to the Office of Graduate Admission as part of the self-managed application, include a statement of interest, official transcripts, a summary information form, TOEFL score (if applicable) and two letters of recommendation. The application deadline for summer and fall admission is April 15; for spring admission it is October 15. A Plan of Study needs to be submitted before matriculation in order to determine the content and duration of the study.

Computational Science Courses

CPS 504 Applied and Computational Mathematics. Prerequisites: CPS 304, and MTH 243 and 424, or instructor's permission. Provides mathematical skills for the development of efficient computational methods for several topics, including: elementary numerical methods and their computer implementations; linear and nonlinear equations; ordinary differential equations; initial and boundary value problems; modeling of data; statistical distributions; generation of random numbers; discrete-event simulations; introduction to stochastic processes; Markov decision chains and applications from transportation, inventory control and health care; and discrete Fourier transforms and its application to digital signal processing. 3 Cr. Fall

CPS 511 Introduction to Embedded Computing: Prerequisites: CPS 202 or CSC 203. Geared towards students who want to combine programming with knowledge of electronic and mechanical workings of embedded systems. Provides an introductory survey on programming and computational algorithm aspects of embedded systems such as cellular phones, space probes, medical devices, and copy machines. Uses high-level languages to review concepts of embedded computing. Includes review of hardware (processor, memory, and peripherals) and software (operating systems, compiling, linking, locating, downloading, debugging, and optimization), as well as examples such as ARCOM Target 188B, and the Xerox copier. 3 Cr. Spring

CPS 517 Introduction to Computational Chemistry: Prerequisites: CHM 206, MTH 203, CPS 201, and PHS 201, or instructor's permission. Provides an introduction to classical and quantum simulation methods as applied to chemistry-related problems and computational chemistry software packages. Covers the topics in three parts. Part I: introductory material, potential surfaces, vibration and electronic properties of molecules, and capabilities/limitations of computational chemistry; Part II: classical molecular simulation methods and molecular dynamics; and Part III: Schrodinger equation, common electronic structure methods, basis sets, geometric optimization, vibrational motion and other molecular properties. 3 Cr. Fall

CPS 521 Introduction to Computational Physics: Prerequisites: PHS 202, MTH 203, and CPS 202 or CSC 203, or instructor's permission. Introduces computational methods commonly used in physics applications, including three of the most famous equations in physics (save, Laplace, and diffusion), as well as classical mechanics. Includes the classical equations of motion, detailed solution of the two-body l/r problem, planetary and astrophysical simulation methods and analysis of simulation data, wave motion and normal coordinate analysis, electromagnetic field and Laplace's equation, molecular simulation (N-body methods, liquid simulation, liquid structure, specification of initial conditions, constant temperature and pressure simulations, Langevin and Brownian dynamics, and correlation functions), diffusion, and percolation. 3 Cr. Fall

CPS 533 Scientific Visualization. Prerequisites: CPS 202 or CSC 203, and MTH 203. Provides concepts and techniques for visualization and its implementation. Emphasizes use of visualization tools in mathematical simulation modeling such as data entry and data integrity, code debugging and code performance analysis, interpretation and display of final results. Provides hands-on experience with visualization software packages in X-Windows environment. May require students to develop a new visualization software designed to aid in the analysis of a chosen problem. Knowledge of programming in a high-level language is essential. 3 Cr. Spring

CPS 541 Computational Methods in Finance: Prerequisites: CPS 202, or CSC 203, MTH 210, and ACC 281 or instructor's permission. Provides an introductory survey of high performance computer modeling and simulation techniques of finance applications. Provides hands-on experience to computational methods and tools such as EXPO and MATLAB Financial Toolbox. Includes methods such as linear algebra, finite difference solution of partial differential equations, artificial intelligence, genetic algorithms, expert systems, and parallel computing method. Includes applications financial market forecasting, trading systems, and asset and option pricing. 3 Cr. Fall

CPS 555 Introduction to Computational Fluid Dynamics: Prerequisites: CPS 202 or CSC 203, and MTH 203, or instructor's permission. Provides a concise introduction to the analytical and computational techniques required of the investigation of fluid flow through computational means. Covers derivation of fundamental equations, dimensional analysis and the Pi theorem; stability of numerical methods; the CFL condition; first, second, and higher order numerical methods; shooting methods; wave equations; parabolic equations; boundary layers; cavity flows; and grid generation. 3 Cr. Fall

CPS 561 Introduction to Computational Biology: Prerequisites: CPS 202 or CSC 203, and BIO 111, or instructor's permission. Provides an introductory survey of the applications of high performance computer modeling and simulation to biological problems. Includes topics such as molecular simulation for structure determination and dynamical properties of biological molecule, and bioinformatics. Uses computational tools such as Biology Benchmark, MATLAB, and AMBER. 3 Cr. Spring

CPS 602 Advanced Computational Software Tools: Prerequisite: CPS 303 or instructor's permission. Covers techniques and software tools and mathematical libraries used on parallel supercomputers. Involves combination of lecture and supercomputer lab. Involves a survey of tools developed by the Ptools Consortium (www.ptools.org) and a study of the software repository by the National High Performance Software Exchange Program (www.nhse.org). Uses case studies involving installation and utilization of both established and research tools in the context of some applications. Demonstrates advanced computational software tools such as Petsc (www.mcs.anl.gov/petsc/) and Globus (www.globus.org) through groundwater modeling applications. Teaches students how to use PetSc and MPI for developing parallel finite element and finite difference application codes. Exposes students to new emerging software tools such as Globus and how it can be used to execute MPI-based applications in heterogeneous meta-computing environments. 3 Cr. Spring

CPS 604 Computational Methods in the Physical Sciences. Prerequisite: CPS 404/504 or MTH 424, or instructor's permission. Trains students in the art and science of the computer solution of partial differential equations (PDE) that commonly arise in scientific applications, and in methods for analyzing results. Covers how to formulate the treatment of applications in which PDEs arise, such as chemistry, physics, biology, ecology, and fluid dynamics. Emphasizes the use of numerical methods commonly used in such applications and of already available software libraries. Entails extensive programming. 3 Cr. Spring

CPS 632 Deterministic Dynamical Systems. Prerequisite: CPS 404/504 or MTH 424, or instructor's permission. Covers modeling and analysis of deterministic dynamical systems found in chemical, biological, fluid dynamics, and other applications. Part I: formulations of classical mechanics, conservation laws, and families of solutions in some model systems. Part II: detailed discussion of simulation methods in chemistry, ecology, biology, fluid dynamics, and other fields. Requires extensive programming. 3 Cr. Fall

CPS 633 Stochastic Dynamical Systems. Prerequisite: CPS 404 or MTH 424. Covers modeling and analysis of stochastic dynamical systems in science, engineering and business applications. Studies random number generators, Monte Carlo method and other stochastic methods in the context of software engineering and pertinent applications in science. 3 Cr. Fall

CPS 644 Supercomputing and Applications. Prerequisites: CPS 303 and 304, or instructor's permission. Covers use of local and remote parallel supercomputers for highly parallel applications such as database operations, weather modeling, engine combustion, groundwater modeling, drug design and human genome problems. Examines efficient parallelization strategies for finite-element and particle-based approaches on SMP and distributed memory architectures. Includes parallel programming standards such as MPI and OpenMP. Examines how to address multiple levels of parallelism through MPI, OpenMP, and tools such as Globus on current and emerging parallel environments such as SMP, distributed memory, and heterogeneous meta-computing environments. Involves a combination of lecture and lab. Requires extensive programming in Fortran 90, High Performance Fortran, C, or C++. Uses communication libraries such as PVM and MPI. 3 Cr. Spring

CPS 698 Graduate Seminar. Prerequisite: Instructor's permission. Provides a forum for the review and discussion of new discoveries and ideas in computational science. Consists of information of topical interest obtained from recent issues of computational science journals. May also include research carried out by students and/or faculty. 1 Cr.

CPS 699 Independent Study. Prerequisite: Instructor's permission. Arranged in consultation with the instructor-sponsor prior to registration. 1-6 Cr.

CPS 700 Project Paper. Prerequisite: Instructor's permission. Targets development of skills for independent research or problem solving in the realm of computational science. Entails a computational project mutually agreed upon between the student and instructor with regular meetings for guidance and feedback. Also requires a written report and 2030 minute presentation. 3 Cr.

  The information in this publication was current as of December 2002 when the text was compiled. Changes, including but not restricted to, tuition and fees, course descriptions, degree and program requirements, policies, and financial aid availability may have occurred since that time. Whether or not a specific course is scheduled for a given term is contingent on enrollment, budget and staffing. The college reserves the right to make any changes it finds necessary and may announce such changes for student notification in publications other than the College catalogs. For the purpose of degree and program completion, students are bound by the requirements in effect as stated in the printed catalog at the time of their matriculation at SUNY Brockport. Inquiries on the current status of requirements can be addressed to the appropriate College department of office. Also refer to the Brockport Web site home page at www.brockport.edu for current information.

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