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Department of Computational Science
129 Smith Hall
(585) 395-2021
Chairperson 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.
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, graduate students learn a core set of skills in mathematics, computer programming, visualization and simulation/modeling, and practice these skills on high performance computers located within the department and at nationwide supercomputing facilities. Graduate students supplement these skills with independent study, culminating in a master's thesis.
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 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 human genetic blueprint 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 program's flexibility allows students to apply math, computer and computational skills to an area of their choice. Scholarships and/or 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 from Silicon Graphics, Inc. The department works 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, Ricoh, the United States Navy, and the Rochester City School District.
Graduate Degree in Computational Science
The Master of Science (MS) in Computational Science requires 30 graduate credits,
including 18 credits of required courses and 12 credits of electives. The program
is appropriate for students with a BS in many fields, including computer science,
math, physics, chemistry, biology, earth sciences, engineering, business and visual
arts.
| Course Number | Course Name | Credits |
|---|---|---|
| (A) Required Courses | ||
| CPS 533 | Scientific Visualization | 3 |
| CPS 602 | Advanced Software Tools | 3 |
| CPS 604 | Computational Methods in the Physical Sciences | 3 |
| CPS 644 | Supercomputing and Applications | 3 |
| Course Number | Course Name | Credits |
|---|---|---|
| (B) Required Research Experience | ||
| CPS 699* | Independent Study | 3 |
| CPS 710 | Thesis | 3 |
| Course Number | Course Name | Credits |
|---|---|---|
| (C) Elective Courses (chosen through advisement) | ||
| Two 500-level or higher graduate courses | 6 | |
| Two 600-level or higher graduate courses | 6 | |
| Total credits (including electives): | 30 | |
| Course Number | Course Name | Credits |
|---|---|---|
| Recommended Electives:** | ||
| CPS 504 | Applied and Computational Mathematics | 3 |
| CPS 517 | Introduction to Computational Chemistry | 3 |
| CPS 521 | Introduction to Computational Physics | 3 |
| CPS 541 | Introduction to Computational Finance | 3 |
| CPS 555 | Introduction to Computational Fluid Dynamics | 3 |
| CPS 632 | Deterministic Dynamical Systems | 3 |
| CPS 633 | Stochastic Dynamical Systems | 3 |
| CPS 699* | Independent Study | 3 |
| CSC 501 | Theory of Programming Languages | 3 |
| CSC 506 | Algorithms and Data Structures | 3 |
| CSC 511 | Computer Architecture | 3 |
| CSC 512 | Operating Systems | 3 |
| CSC 519 | Computer Networks | 3 |
| CSC 521 | Computer and Network Security | 3 |
| CSC 522 | Relational Database Design | 3 |
| CSC 527 | Software Engineering | 3 |
| CSC 529 | Object-oriented Programming | 3 |
| CSC 534 | Artificial Intelligence | 3 |
| CSC 542 | Electronic Commerce Technology | 3 |
| CSC 544 | Introduction to Parallel Computing | 3 |
| CSC 583 | Theory of Computation | 3 |
| MTH 521 | Number Theory | 3 |
| MTH 542 | Statistical Methods II | 3 |
| MTH 546 | Probability and Statistics II | 3 |
| MTH 551 | Advanced Calculus | 3 |
| MTH 556 | Advanced Differential Equations | 3 |
| MTH 561 | Deterministic Mathematical Models | 3 |
| MTH 562 | Stochastic Mathematical Models | 3 |
| MTH 571 | Numerical Analysis | 3 |
| MTH 581 | Discrete Mathematics II | 3 |
| MTH 621 | Algebra | 3 |
| MTH 628 | Applications of Algebra | 3 |
| MTH 641 | Mathematical Statistics | 3 |
| MTH 651 | Real Analysis | 3 |
| MTH 659 | Topics in Analysis | 3 |
| MTH 669 | Topics in Applicable Mathematics and Statistics | 3 |
**3 credits of CPS 699 are required, but up to nine credits total may be taken.
**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 paper-based version of the Test
of English as a Foreign Language (TOEFL), at least 213 on the computerized version
or at least 79-80 on the TOEFL IBT version. Applicants must have a 3.0 GPA; however,
conditional admission may be granted in unusual cases. Application materials are to
be submitted to the Office of Graduate Admission as part of the self-managed application
and must include a statement of interest, official transcripts, TOEFL score (if applicable)
and two letters of recommendation. A Plan of Study, worked out between each student and his or her advisor, must be submitted before
the end of the first semester of study.