Department of Computational Science

Main Page Content

Department of Computational Science

129 Smith Hall
(585) 395-2021

Chair and Associate Professor: Robert E. Tuzun, PhD, University of Illinois/Urbana-Champaign; Empire Innovation Professor: Osman Yasar, PhD, University of Wisconsin/Madison; Associate Professor: Leigh J. Little, PhD, Arizona State University; Assistant Professor: Wensheng Shen, PhD, University of Kentucky.


Combined BS/MS Program


Along with traditional experimental and theoretical methodologies, advanced work in all areas of science and engineering has come to rely critically on computation. Computer modeling combined with visualization represents a new paradigm for scientific exploration and technological research and development. It permits a new approach to problems that were previously inaccessible. The goal of the computational science program is to enable students to perform computational modeling in problems of technological and societal relevance. To this end, students learn a core set of skills in mathematics, computer programming, visualization, and simulation/modeling. Students may then apply these skills to application areas of interest to them.

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 safer 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. Economists use computers to predict future behavior of many financial systems, including the stock market. Computer modeling enables the study and performance testing of systems before they are put into production. This approach has saved billions of dollars and years of development time.

The Department of Computational Science has received equipment support from Intel and Silicon Graphics and works closely with local industry, particularly Xerox Corporation and Eastman Kodak Company. The program is flexible so as to allow students to follow their particular interests and continue, if desired, with advanced degrees. Graduates can expect employment in industry, government, business, academia, and at major research and development laboratories.

Major in Computational Science

The computational science undergraduate major requires 36 credits of the following courses from the Departments of Computational Science, Computer Science, and Mathematics and from the department of an application area of interest. Six additional credits of elective courses are required.

(a) Required Courses Credits
MTH 203 Calculus III 4
MTH 243 Elementary Statistics 3
MTH 324 Linear Algebra 3
CSC 203 Fundamentals of Computer Science I 4
CPS 201 Computational Tools I 3
CPS 202 Computational Tools II 3
CPS 303 High Performance Computing 3
CPS 304 Simulation and Modeling 3
CPS 404 Applied and Computational Mathematics 3
(b) Elective Courses
200-level and higher non-CPS courses from an area of application chosen under advisement 12
Upper-division elective courses 6
    Total credits (including electives): 47
(c) Prerequisites
Calculus I and II (MTH 201 and 202—8 credits)
Discrete Mathematics I (MTH 281—3 credits)
Introduction to Computer Science (CSC 120—3 credits)

Minor in Computational Science
(a) Required Courses Credits
CPS 201 Computational Tools I 3
CPS 202 Computational Tools II 3
CPS 303 High Performance Computing 3
CPS 304 Simulation and Modeling 3
(b) Elective Courses
200-level and higher courses in math and sciences chosen under advisement 8
    Total Credits (including electives): 20
(c) Prerequisites:
Calculus III (MTH 203—4 credits)

Combined BS/MS Program in Computational Science

The combined BS/MS degree is designed for high-parameter students wishing to accelerate the pace of their studies and to receive bachelor's and master's degrees in computational science within five years. To be considered for entry into this program requires a GPA of at least 3.25, a written application, and interviews with the departmental undergraduate and graduate directors. In addition to the required courses listed above, the combined program requires undergraduate electives, duplicate requirements (simultaneously satisfying undergraduate elective and graduate core requirements), research experience, and graduate electives.

(a) Elective Courses Credits
200-level and higher non-CPS courses from an area of application chosen under advisement
(b) Duplicate Requirements
  Scientific Visualization
  Advanced Software Tools
  Computational Methods in the Physical Sciences
  Supercomputing and Applications
(c) Research Experience
  Graduate Seminar
  Independent Study
* 3 credits of CPS 699 are required, but up to 9 total may be taken
(d) Elective Courses (chosen through advisement)
Four 600-level or higher graduate courses
Note: Information on graduate courses and electives may be found in the SUNY Brockport 2007-2009 Graduate Studies Catalog.

Computational Science Courses

CPS 101 Introduction to Computation (A,N). Prerequisites: MTH 121 or instructor’s approval. An introduction to computation as used in science and engineering. Emphasizes practical applications of formulas to real-life problems and on tools for their solution. Topics include: (1) some basic techniques used in computational modeling (linear regression for data-fitting, determination of areas and volumes, rate of change, and use of graphical calculator), (2) essentials of programming in FORTRAN 90; and (3) essentials of the UNIX operating system (basic commands, editors, file manipulation). 3 Cr.

CPS 201 Computational Tools I (A). Prerequisites: CSC 120 or CPS 101. An introduction to fundamental concepts of computational science using the Fortran 90 programming language, and the clear and concise written presentation of scientific results. Topics include: the Fortran 90 language, program construction and debugging, consequences of finite precision arithmetic, basic machine constants, and modeling of simple physical situations. May also include other modeling tools such as Stella, Agent Sheets, and Project Interactivate. Extensive programming required. 3 Cr.

CPS 202 Computational Tools II (A). Prerequisite: CPS 201. A continuation of CPS 201. Emphasizes commonly encountered scientific programming libraries (BLAS, LAPACK, ATLAS). Model problems in numerical linear algebra are heavily utilized. Topics include: advanced topics in Fortran 90 Programming (data structures, overloaded functions, dynamic memory allocation), programming in MATLAB, use of the UNIX operating system, use of the BLAS, LAPACK and ATLAS libraries, optimization of programs (by hand and via compiler optimization), and technical writing. Extensive programming in Fortran 90 and MATLAB required. 3 Cr.

CPS 300 Internet and Technology Ethics (A,I). The Internet has rapidly become a primary source of information, communication and entertainment for society. However, the rapid expansion has resulted in numerous issues that can adversely affect all Internet users. More importantly, new regulations are being passed that can expose users to significant legal risks. Fundamental legal principles that affect all users of the Internet will be discussed and analyzed. 3 Cr.

CPS 301 Issues in Criminal and Forensic Computing (A,I). A discussion of issues related to the use of computers in the criminal justice system. Discussions of growing capabilities in and ramifications of such areas as forensic computing, criminal profiling, fingerprint identification, video image processing, and simulation of crime scenes. In addition, discussions of emerging and future trends in the use of computers as a crime fighting tool. 3 Cr.

CPS 302 Society, Science and Technology (A,I). Discusses ways society and science have affected each other. Introduces a historical perspective of this relation for the past several decades, including the contemporary society. Identifies trends and changes within science and technology in relation to the larger society. Students will attend lectures, discuss issues, and write essays. 3 Cr.

CPS 303 High Performance Computing (A). Prerequisite: CPS 202. An introduction in applied parallel computing, using the Message Passing Interface (MPI) standard for parallel communication. Topics include: parallel architectures, problem decomposition, extracting parallelism from problems, benchmarking and performance of parallel programs, applications to the sciences, and technical writing. Extensive programming in Fortran 90 and/or C/C++ required. 3 Cr.

CPS 304 Simulation and Modeling (A). Prerequisites: CPS 202 and MTH 203; and either MTH 243 or MTH 346. An introduction to stochastic and deterministic methods used to simulate systems of interest in a variety of applications, with emphasis on problem set-up and analysis and programming methods. Part I: discrete event simulation and statistical analysis of results. Part II: other examples of stochastic simulations such as the spread of forest fires. Part III: deterministic methods for particle simulations, with examples from astronomical and molecular simulation. In addition, a brief discussion of the simulation of continuous media. Extensive programming required. 3 Cr.

CPS 404 Applied and Computational Mathematics (A). Prerequisites: CPS 304 and MTH 203; and either MTH 243 or MTH 346. A survey of scientific computing methods, emphasizing programming methods, interpretation of numerical results, and checks for numerical sensibility and self-consistency. The course is divided into several modules, including: (1) representation of floating point data, truncation and rounding error, and basic considerations for accurate numerical computation; (2) iterative numerical methods; (3) numerical differentiation and integration; (4) numerical interpolation; (5) random number generation; (6) the Fast Fourier Transform; and (7) numerical solution of ordinary differential equations. Extensive programming required. 3 Cr.

CPS 417 Introduction to Computational Chemistry (A). Cross-listed as CHM 417. An introduction to classical and quantum simulation methods as applied to chemistry-related problems and computational chemistry software packages. Part I: introductory material, potential energy surfaces, vibrational and electronic properties of molecules, and capabilities/limitations of computational chemistry. Part II: classical molecular simulation methods, molecular dynamics, molecular mechanics, Monte Carlo calculations, normal coordinate analysis, computer “measurement” of materials properties. Part III: the Schrodinger equation, common electronic structure methods, basic sets, geometric optimization, and molecular properties. 3 Cr.

CPS 461 Introduction to Computational Biology (A). Prerequisites: CPS 202, BIO 111 and CHM 206. 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.

Last Updated 8/19/19

Close mobile navigation