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Ph.D. In Computational Sciences and Informatics

Overview of the Degree

Founded in 1992, the innovative Computational Sciences and Informatics (CSI) doctoral program at George Mason University addresses the role of computation in science, mathematics, and engineering. Computational Sciences is defined as the development and application of computational methodologies and techniques to the modeling, simulation, and understanding of phenomena in the natural sciences and engineering. Informatics is defined as the design and implementation of complex software systems for the extraction of knowledge from large databases. The research and teaching activities associated with the CSI program reflect the recognized role of computation as part of a triad with theory and experimentation, leading to a better understanding of nature.

Areas of Concentration

Research opportunities leading to the doctoral degree are available in each of the following Areas of Concentration:

  • Computational Fluid Dynamics
  • Computational Learning
  • Computational Materials and Chemical Sciences
  • Computational Mathematics
  • Computational Physics
  • Computational Statistics
  • Quantum Information Science
  • Space Sciences and Computational Astrophysics
  • Computational Remote Sensing

Students may also pursue interdisciplinary research that combines the areas of concentration listed above with each other and also with computational neuroscience, climate dynamics, bioinformatics and remote sensing, which are now separate Ph.D. programs within COS.

The CDS Department maintains several weekly colloquia and seminar series to ensure that students are exposed to the latest developments at area research institutions. Doctoral students are encouraged to participate in national and international meetings where they can present their latest findings.

Program of Study

The list of research concentrations tells only part of the story, because the greatest strength of the CSI doctoral program lies in its ability to foster and promote truly interdisciplinary research that crosses traditional domain boundaries. In the CSI doctoral program, each student is presented with an exciting opportunity to create a new area of interdisciplinary inquiry that would not fit into a traditional Ph.D. program. Students in the CSI doctoral program use computationally intensive methods to solve current problems in these scientific areas.

The doctoral program combines three intellectual elements:

  1. core computational science topics;
  2. computational intensive courses in specific scientific areas;
  3. research leading to the dissertation.

The doctoral program is designed to be completed in 4-5 years including:

  1. 12 hours of core computational courses (scientific computing, databases, visualization);
  2. 15 hours from concentration courses in one of the science areas;
  3. 18 hours in electives from science courses, with at least 9 credits of CSI courses;
  4. 3 hours of 1-credit seminar courses;
  5. 24 hours in dissertation research.

Admission Requirements

Students interested in applying for admission into the CSI Ph.D. program should have a bachelor's degree in any natural science, mathematics, engineering, or computer science with a minimum GPA of 3.00 in their last 60 credits of study. All applicants to the Ph.D. program should have a mathematics background up to and including Differential Equations. All applicants to the Ph.D. program should also have knowledge of a computer programming language such as C, C++, FORTRAN, etc.

The GRE exam is required, unless the applicant holds a Master's degree from a school in the United States. A TOEFL score of 575 (paper-based exam) or 230 (computer-based exam) is required for international students. The ETS code for GMU is 5827

Students should submit a completed Graduate Application along with three letters of recommendation, an expanded goals statement and a $50 check to cover the application fee (payable to George Mason University) in addition to the items listed above.

Applications should be received by March 1 for Fall Semester and November 1 for Spring Semester. Applications requesting support must be received by February 1 for the Fall semester. Please note that local applications may be accepted after these general deadlines.

Please send completed applications to the address below:

COS Graduate Applications Processing Center
George Mason University
Mail Stop 6A3
Fairfax, VA 22030-4444

Additional information:

Phone: (703) 993-1988; Fax: (703) 993-9300; e-mail: blaisten@gmu.edu

 

Curriculum Requirements

  1. General core course requirements. 12 credits from the following:
    1. CSI 700 Numerical Methods
    2. CSI 701 Foundations of Computational Science
    3. CSI 702 High Performance Computing
    4. CSI 703 Scientific and Statistical Visualization
    5. CSI 710 Scientific Databases
  2. Concentration core requirements. 15 credits in one of the following concentrations:
    1. Computational Fluid Dynamics
      1. CSI 720 Fluid Mechanics
      2. CSI 721 Computational Fluid Dynamics I
      3. CSI 722 Computational Fluid Dynamics II
      4. CSI 742 The Mathematics of the Finite Elements Method
      5. One from: CSI 685 Fundamentals of Materials Science, CSI 729 Topics in Continuum
        Systems, CSI 780 Computational Physics and Applications, CSI 786 Molecular Dynamics
        Modeling, CSI 787 Computational Materials Science, CSI 789 Mechanics of Solids
    2. Computational Learning
      1. CSI 771 Computational Statistics
      2. CSI 772 Statistical Learning
      3. CSI 773 Statistical Graphics and Data Exploration
      4. CSI 777 Principles of Knowledge Mining
      5. CSI 873 Computational Learning and Discovery
    3. Computational Materials and Chemical Sciences
      1. CSI 685 Fundamental of Materials Science or CSI 687 Solid State Physics
        and Applications
      2. CSI 780 Computational Physics and Applications
      3. CSI 783 Computational Quantum Mechanics
      4. CSI 787 Computational Materials Science
      5. One from: CSI 786 Molecular Dynamics Modeling, CSI 789 Mechanics of Solids,
        CSI 885 Atomistic Modeling of Materials
    4. Computational Mathematics
      1. CSI 742 The Mathematics of the Finite Elements Method
      2. CSI 747 Nonlinear Optimization and Applications
      3. Three from: MATH 677 Ordinary Differential Equations, MATH 678 Partial Differential
        Equations, CSI 740 Numerical Linear Algebra, CSI 746 Wavelet Theory,
        CSI 772 Statistical Learning
    5. Computational Physics
      1. CSI 780 Computational Physics and Applications
      2. CSI 783 Computational Quantum Mechanics
      3. Three from: CSI 782 Statistical Mechanics for Modeling and Simulation,
        CSI 784 Quantum Mechanics, CSI 785 Electromagnetic Theory,
        CSI 786 Molecular Dynamics Modeling, CSI 787 Computational Material Science
    6. Computational Statistics
      1. CSI 771 Computational Statistics or CSI 773 Statistical Graphics
        and Data Exploration
      2. CSI 778 Real Analysis and Statistics
      3. CSI 876 Measure and Linear Spaces or CSI 877 Geometric Methods in Statistics
      4. CSI 972 Mathematical Statistics I
      5. CSI 973 Mathematical Statistics II
    7. Quantum Information Science
      1. CSI 615 Quantum Computation
      2. CSI 715 Quantum Complexity Theory
      3. CSI 716 Quantum Information Theory
      4. CSI 717 Quantum Computer Programming or CSI 718 Quantum Computer Realization
      5. CSI 783 Computational Quantum Mechanics or CSI 784 Quantum Mechanics
    8. Space Sciences and Computational Astrophysics
      1. CSI 785 Electromagnetic Theory
      2. Two from: CSI 661 Astrophysics, CSI 662 Space Weather, CSI 783 Computational
        Quantum Mechanics, CSI 784 Quantum Mechanics
      3. One from: ASTR 760 Space Plasma Physics, CSI 782 Statistical Mechanics
        for Modeling and Simulation
      4. One from: CSI 721 Computational Fluid Dynamics I, CSI 761 N-Body Methods and
        Particle Simulations, CSI 780 Computational Physics and Applications, CSI 788
        Simulations of Large-Scale Physical Systems
    9. Computational Remote Sensing
      Select five from:
      1. EOS 740 Hyperspectral Imaging Systems
      2. EOS 747 Satellite Data Reception and Product Generation
      3. EOS 753/ CSI 753 Observations of the Earth and its Climate
      4. EOS 754/ CSI 754 Earth Science Data and Advanced Data Analysis
        (formerly Earth Observing/Remote Sensing Data and Data Systems)
      5. EOS 756 Physical Principles of Remote Sensing
      6. EOS 757/ CSI 757 Techniques and Algorithms in Earth Observing and Remote Sensing
      7. EOS 758 Digital Processing of Remote Sensing Imagery
      8. EOS 760 Remote Sensing Applications
      9. EOS 840/CSI 854 Hyperspectral Imaging Applications
  3. Science Electives: 18 credits, with at least 9 credits of CSI courses
  4. Seminars: 3 credits of CSI 898, 899, 991
    (any of these series can be repeated three times or more)
  5. Dissertation Research: 24 credits

Maryland Academic Common Market

The CSI Ph.D. degree has been approved for participation in Maryland's Academic Common Market (ACM). The ACM allows full-time students who are residents of Maryland to enroll in the CSI Ph.D. program while paying the in-state VA tuition rate, which is about one-third of the out-of-state tuition rate that residents of Maryland would otherwise have to pay. For full details regarding Maryland's ACM program, click here The ACM program code for the CSI Doctoral Program is 300801. Interested students should contact Elizabeth Stille.