Doctor of Philosophy in Computational Sciences and Informatics
(Banner code: SC-PHD-CSI)
Founded in 1992, the Ph.D. in Computational Sciences and Informatics (CSI) addresses the role of computation and quantitative analysis of data in the sciences, applied mathematics, and engineering. Computational sciences are defined as the systematic development and application of computational algorithms and techniques for modeling and simulation of scientific and engineering phenomena. Informatics is defined as the systematic development and application of methods for mining and analyzing large datasets obtained by experiment, modeling, databases, and observation. The resulting interdisciplinary approach leads to understanding, interpretation and prediction of phenomena that traditional theory and experiment alone cannot provide. The close relationship of the CSI Ph.D. to research and development activities in federal laboratories, scientific institutions, and high-technology firms gives graduates opportunities for new employment and professional advancement.
The schedule of classes accommodates part-time students with courses meeting once a week in the late afternoon or early evening. Research and teaching activities associated with the program reflect the recognized role of computation for better understanding of nature as part of a triad with theory and experiment.
The 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 exciting opportunities of interdisciplinary research fundamentally different from traditional Ph.D. programs.
The Department of Computational and Data Sciences (CDS) offers 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.
George Mason University graduate admission requirements and specific College of Science admission requirements (including deadlines) apply. Additionally, all applicants, including Mason undergraduates and graduates, must submit the following:
- Official transcript of undergraduate and graduate course work. Applicants 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 PhD program should have a mathematics background up to and including differential equations. All applicants to the PhD program should also have knowledge of a computer programming language such as C, C++, FORTRAN, etc.
- For applicants whose official language is not English, official TOEFL scores that meet the minimum requirements in the College of Science: 570 (paper-based test), or 230 (computer-based test), or 88 points total and a minimum of 20 points in each section (Internet-based test). The ETS code for Mason is 5827
- GRE Scores: The GRE scores are waived if the applicant has a master’s degree from an accredited university in the U. S.
- Three letters of recommendation from individuals knowledgeable about the professional and/or academic work of the applicant
- Recent professional resume
- Statement of interest narrative that includes a description of career and research goals, personally developed skills, Ph.D. emphasis area of major interest, and eventual contacts made with departmental faculty.
Applicants to the Ph.D. program who have completed a master’s degree in computational science, mathematics, engineering, or natural sciences are eligible for admission. Outstanding applicants with extensive, advanced post B.S. work experience may be considered for admission.
Exceptionally qualified students without a related bachelor’s or master’s degree may be admitted provisionally and required to take additional undergraduate and/or graduate courses prescribed by the department graduate committee.
Admission decisions are based on applicant’s qualifications and the availability of faculty expertise in the area of research the applicant expects to pursue. All application materials are reviewed by the department doctoral committee and decisions are made with input from appropriate faculty members.
Financial support for outstanding applicants is available through fellowships as well as research and teaching assistantships. For best consideration, applicants are encouraged to apply early and to contact potential faculty members expressing their interest in support.
For additional information contact the CSI graduate coordinator.
Reduction of Credit
Students must complete a minimum of 72 graduate credits, which may be reduced by a maximum of 24 credits from a completed Master in Computational Science or other related field. Reduction of credit requires the approval of the CSI graduate coordinator and the dean (or designee) of the College of Science. They determine the number of credits to be reduced and whether these credits are eligible for reduction and applicable to the CSI program. Eventual reduction of credits becomes effective when the student is advanced to Ph.D. candidacy.
Program of Study
The CSI Ph.D. entails 72 graduate credits, which include 48 credits of graduate coursework and 24 credits of dissertation research.
The 72-credit doctoral program combines three intellectual elements:
- Core computational science topics
- Computational intensive courses in specific scientific areas
- Research leading to the dissertation
The doctoral program, designed to be completed in 4 to 5 years, includes the following requirements:
- 6 credits of core computational courses (scientific computing, databases, visualization)
- 18 credits of approved courses consistent within an area of emphasis selected from CSI courses listed in the catalog
- 1-3 credits of CSI colloquium/seminar
- 21-23 advisor approved electives
- 24 credits of dissertation research
Students must satisfy all requirements for doctoral degrees expressed in the Academic Policies section of the University.
Doctoral Coursework (48 credits)
General Core Courses (6 credits):
Select from the following:
- CSI 690 – Numerical Methods Credits: 3
- CSI 695 – Scientific Databases Credits: 3
- CSI 702 – High-Performance Computing Credits: 3
- CSI 703 – Scientific and Statistical Visualization Credits: 3
Areas of Emphasis (18 credits):
- Computer Modeling and Simulation including applications to the natural sciences
- Data Science including computational learning, statistics, and data analytics
Students may also pursue interdisciplinary studies that combine the emphases listed above. Six CSI courses (18 credits) are required and should be selected from the list below, not repeating the core courses, and including at most one 500-level course:
- CSI 500 – Computational Science Tools
- CSI 501 – Introduction to Scientific Programming
- CSI 654 – Data and Data Systems in the Physical Sciences
- CSI 672 – Statistical Inference
- CSI 674 – Bayesian Inference and Decision Theory
- CSI 676 – Regression Analysis
- CSI 678 – Times Series Analysis and Forecasting
- CSI 685 – Fundamentals of Materials Science
- CSI 690 – Numerical Methods
- CSI 695 – Scientific Databases
- CSI 701 – Foundations of Computational Science
- CSI 702 – High-Performance Computing
- CSI 703 – Scientific and Statistical Visualization
- CSI 709 – Topics in Computational Sciences and Informatics
- CSI 721 – Computational Fluid Dynamics I
- CSI 739 – Topics in Bioinformatics
- CSI 740 – Numerical Linear Algebra
- CSI 742 – The Mathematics of the Finite Element Method
- CSI 744 – Linear and Nonlinear Modeling in the Natural Sciences
- CSI 747 – Nonlinear Optimization and Applications
- CSI 754 – Earth Science Data and Advanced Data Analysis
- CSI 758 – Visualization and Modeling of Complex Systems
- CSI 771 – Computational Statistics
- CSI 772 – Statistical Learning
- CSI 773 – Statistical Graphics and Data Exploration
- CSI 777 – Principles of Knowledge Mining
- CSI 780 – Computational Physics and Applications
- CSI 782 – Statistical Mechanics for Modeling and Simulation
- CSI 783 – Computational Quantum Mechanics
- CSI 786 – Molecular Dynamics Modeling
- CSI 787 – Computational Materials Science
- CSI 788 – Simulation of Large-Scale Physical Systems
- CSI 873 – Computational Learning and Discovery
- CSI 876 – Measure and Linear Spaces
- CSI 877 – Geometric Methods in Statistics
Colloquium/Seminar (1-3 credits):
The Department of Computational and Data Sciences offers 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.
Electives (21-23 credits):
If necessary, students take elective courses in consultation with their assigned advisor for completing the 48 credits of coursework. Elective courses allow for interdisciplinary studies leading to research that combines the two program emphases with each other and also with bioinformatics, chemistry, climate dynamics,computational biology, computational social science, geo-information science, mathematics, or physics. Most of these areas are autonomous doctoral programs within the College of Science.
Doctoral Research (24 credits)
No more than 24 combined credits from CSI 998 and CSI 999 may be applied toward satisfying doctoral degree requirements, with no more than 18 credits of CSI 998.
- CSI 998 – Doctoral Dissertation Proposal Credits: 1-12
- CSI 999 – Doctoral Dissertation Credits: 1-12 (minimum 3 credits at first registration)
Students become eligible to register for CSI 998 upon having an approved dissertation committee. Upon advancement to doctoral candidacy, students are eligible to register for CSI 999.
Degree Total: 72 credits
Students must form their dissertation committee nearing a successful completion of the coursework requirement. First, the student identifies a dissertation director willing to advise the dissertation research. Next, the student identifies at least three additional committee members in consultation with the dissertation director. The committee composition must have at least two full-time instructional faculty members of the CDS department and at least one Mason instructional faculty member from outside the CDS department. All committee members must belong to the Mason graduate faculty, must hold earned doctorates, and possess knowledge and experience in the student’s chosen dissertation topic. The CSI graduate coordinator and the College of Science dean (or delegate) must approve the full composition of the dissertation committee before the student is allowed to register for CSI 998 Dissertation Proposal.
Students must successfully complete separate written, computational, and oral examinations prepared and administered by their dissertation committee.
Dissertation Proposal Preparation and Advancement to Candidacy
Students advance to doctoral candidacy by fulfilling the following requirements:
- The student must successfully complete candidacy examinations as stated above.
- The student prepares a dissertation proposal describing in detail the planned dissertation research. The proposal must be approved by the dissertation committee.
- Following successful completion of the research proposal and candidacy exams, the committee will recommend the student for advancement to doctoral candidacy.
Dissertation Research and Defense
After advancing to candidacy, the student will work on a doctoral dissertation while enrolled in CSI 999. The dissertation is a written piece of original research that demonstrates a doctoral candidate’s mastery of the subject matter. A student is expected to produce new and original research worthy of publication in a peer-reviewed journal. After the dissertation is completed, the committee will review the dissertation and examine the student in a public oral dissertation defense.