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Graduate Record 2016-2017 [ARCHIVED RECORD]
Systems Engineering
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 Return to: School of Graduate Engineering and Applied Science
The department offers three graduate degrees: Master of Engineering, Master of Science, and Doctor of Philosophy. The plan of study is always tailored to the individual needs and interests of the student; however, each student must gain the knowledge of the fundamental methodologies and techniques of systems engineering.
The M.E. student first learns the fundamentals of systems analysis, design, and integration, and applies this knowledge to an ME project (non-thesis option).
The M.S. student first learns the fundamentals of systems, decision, and information sciences, and next applies this knowledge to a more focused research project leading to a master’s thesis.
The Ph.D. student first acquires the advanced knowledge in one area of systems, decision, and information sciences, and next contributes to knowledge through research leading to a doctoral dissertation.
Current basic research in the department explores theoretical and methodological issues in the following areas: computational statistics, performance evaluation, capacity assurance, and resource allocation; multivariate systems monitoring; discrete event simulation; probabilistic modeling, empirical model building, data fusion, and data mining; risk assessment and management; learning algorithms; optimization, dynamic programming, and Markov decision processes; Bayesian forecasting and decision theory; cognitive systems engineering, human-computer interaction, decision support systems design, control theory and systems integration.
Research Projects M.S. and Ph.D. students typically associate with an ongoing research project in the department. These projects involve both theoretical and applied elements and allow students to work closely with faculty on challenging, contemporary problems. Examples of current research projects include network optimization, intelligent transportation system, air traffic prediction system, probabilistic forecasting of weather, flood warning system, spatial knowledge discovery, regional crime data analysis, clinical and biological data integration, critical safety data analysis, mitigation of risk to cyber and physical infrastructure, credit scoring and credit portfolio management, valuation of intellectual property, design of hospital systems, and airline cockpit displays, and supervisory control of unmanned vehicles.
Degree Programs for Working Professionals The Department of Systems and Information Engineering offers two programs specifically designed for working professionals.
The Accelerated Master’s Program in Systems Engineering (AMP) enables working professionals to earn a Master of Engineering degree in one year while continuing to work full time. The practice-oriented degree has a focus on systems thinking and data analytics, broadly applicable skills which are in strong demand. The curriculum is augmented by business topics taught by faculty from the Darden Graduate School of Business. Class meetings on Grounds give students the advantage of interacting face-to-face with full-time faculty and cohort of talented classmates in a focused learning environment. Working together in small groups and sharing the perspectives of a diverse cohort of experienced engineers lead to long-lasting friendships and a strong professional network among members of the cohort and AMP alumni.
The accelerated schedule includes one week in residence in late May, twenty alternate weekends (all day Fridays and Saturdays) over the next ten months, and a final week in residence the following April. Comprehensive tuition includes courses and fees, books, software, and meals and lodging while the cohort is on grounds for classes. Financial aid is available in the form of education loans.
The Department of Systems and Information Engineering participates in the Commonwealth Graduate Engineering Program (CGEP) by presenting graduate-level courses in a distributed learning environment. CGEP students achieve a Master of Engineering degree. CGEP students participate in live class sessions alongside their student peers sitting in the classroom, accessing the interactive sessions via their computer and Internet connection. Class sessions are also recorded for later viewing/reviewing.
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Masters of Engineering
Master of Engineering (M.E.) is a graduate professional degree for those wishing to pursue careers in industry, consulting, or government. Our program is designed to provide a blend of fundamental knowledge and professional skills needed by
- practicing systems engineers,
- management engineers,
- entrepreneurial engineers.
It is an intensive, non-thesis, 12-month program built of five components.
Degree Requirements
A candidate for the Master of Engineering degree must fulfill the general requirements of the School of Engineering and Applied Science and must complete an approved plan of study consisting of at least 32 credit hours. Required Credits
The plan of study must include at least 32 credit hours of graduate-level work and must satisfy the following requirements.
- 9 credit hours of core courses SYS 6001, SYS 6043 or SYS 6003, SYS 6005 or SYS 6045
- 18 or more credit hours of elective courses distributed thusly:
- At least 9 credit hours of systems engineering courses at the 6000 or 7000 level. These credit hours cannot be earned through Independent Study SYS 6993 and SYS 7993, Supervised Project Research SYS 6995 and SYS 8995. Students enrolled in the Accelerated Master’s Program complete SYS 6002, Systems Integration, in lieu of SYS 8995.
- No more than 3 credit hours of Independent Study SYS 6993 or SYS 7993
- No more than 3 credit hours at the 5000-level from the School of Engineering and Applied Science. (The 5000-level courses in the Graduate School of Arts and Sciences are nominally equivalent to 6000-level courses in the School of Engineering and Applied Science.)
- 2 or more credit hours of Systems Engineering Colloquium, SYS 7096. The student should register for one credit hour in each semester, the Fall semester and the Spring semester. Students enrolled in the CGEP Master’s of Engineering Program take a 2 or 3 credit elective in lieu of SYS 7096, typically SYS 8995.
- 3 or more credit hours of Supervised Project Research, SYS 8995. The student must complete a project under the guidance of a faculty advisor. It should be a state-of-the-art application of systems engineering methodology or technique to a real-world problem, documented in a written report. Students enrolled in the Accelerated Master’s Program complete SYS6002, Systems Integration, in lieu of SYS 8995.
Fall Semester
Nominal plan of study for on-grounds students.
Credits: 13
Spring Semester
Credits: 13
SYS xxxx Systems Engineering Elective Credits: 3
SYS xxxx Systems Engineering Elective Credits: 3
SYS xxxx Systems Engineering Elective Credits: 3
XXX XXXX Elective Credits: 3
Minimum total number of credit hours 32
Master of Science
Master of Science (M.S.) is a graduate degree for those wishing not only to acquire fundamental knowledge, but also to contribute to the advancement of knowledge through independent, original research. The program prepares students for careers as practicing systems engineers or research engineers, and serves as a stepping stone towards the doctorate. The program consists of five components.
- Core courses supplying the fundamentals of systems and decision sciences.
- Elective courses through which the student can expand and deepen the knowledge relevant to his/her research.
- Colloquium, a regular meeting of graduate students and faculty for presenting and discussing contemporary systems problems and research.
- Research conducted individually, under the guidance of a faculty advisor, and leading to a master’s thesis and a technical paper.
- Participation in the intellectual life of the University.
NOTE: This is the typical schedule for on-grounds M.E. students. The Accelerated Master’s Program (AMP) operates on a different schedule in which two courses are completed in parallel over five weekends within a 10 week period. See the AMP website for the current academic year calendar at http://amp.sys.virginia.edu.
Degree Requirements
A candidate for the Master of Science degree must fulfill the general require- ments of the School of Engineering and Applied Science and the following specific requirements.
- Complete an approved plan of study consisting of at least 32 credit hours.
- Present satisfactorily a thesis proposal.
- Author or coauthor at least one manuscript of a technical paper.
- Defend satisfactorily a thesis.
Required Credits
The plan of study must include at least 32 credit hours of graduate-level work and must satisfy the following requirements.
- 9 or more credit hours of core courses distributed thusly:
- At least one course in the “methodological” aspects of systems engineering: SYS 6001, SYS 6021, SYS 6023, SYS 6050, SYS 7001
- At least one course in the “optimization” aspects of systems engineering: SYS 6003, SYS 7042
- At least one course in the “stochastic” aspects of systems engineering: SYS 6005, SYS 6018, SYS 6034
- 15 or more credit hours of elective courses distributed thusly:
- At least 6 credit hours of systems engineering courses at the 6000 or 7000 level. (These credit hours cannot be earned through Independent Study SYS 6993 and SYS 7993, Supervised Project Research SYS 6995 and SYS 8995, Graduate Teaching Instruction SYS 8997 and SYS 9997, Thesis SYS 8999, and Dissertation SYS 9999.)
- No more than 3 credit hours of Independent Study SYS 6993 or SYS 7993
- No more than 3 credit hours at the 5000 level from the School of Engineering and Applied Science. (The 5000-level courses in the Graduate School of Arts and Sciences are nominally equivalent to 6000-level courses in the School of Engineering and Applied Science.)
- 2 or more credit hours of Systems Engineering Colloquium, SYS 7096.The student should register for one credit hour in each semester of the first year of study
- 6 or more credit hours of Thesis, SYS 8999.
Nominal Plan of Student
(When the student serves as a Teaching or Research Assistant)
Summer Session
- SYS xxxx Teaching or Research Credits: 3
Spring Semester
- SYS XXXX System Engineering Elective Credits: 3
- SYS xxxx Elective Credits: 3
- SYS xxxx Elective Credits: 3
- SYS xxxx System Engineering Colloquium Credits: 1
Fall Semester
- SYS xxxx Elective Credits: 3
- SYS xxxx Elective Credits: 3
- SYS xxxx Teaching or Research Credits: 3
Minimum total number of credit hours 32
Doctor of Philosophy
Doctor of Philosophy (Ph.D) is an advanced graduate degree for those wishing to contribute to knowledge through independent, original research at the cutting edge of systems engineering. The program provides a springboard for careers as academicians, researchers, consultants, and higher-level engineering managers in universities, institutes, industry, and government.
Doctoral students should possess initiative, inquisitiveness, ingenuity, and perseverance. Our program affords each student the flexibility to design a plan of study that fulfills the individual’s career objectives and intellectual aspirations. The primary concern of the faculty is to give each student guidance to and opportunity for a complete educational experience and superior professional preparation. Towards that end, the program includes four components.
- Courses through which the student acquires fundamental and advanced knowledge
- Colloquium, a regular meeting of graduate students and faculty for presenting and discussing contemporary systems problems and research
- Research conducted individually, under the guidance of an advisory committee, and leading to a doctoral dissertation and scholarly papers
- Participation in the intellectual life of the University.
Degree Requirements
A candidate for the Ph.D. degree must fulfill the general requirements of the School of Engineering and Applied Science and the following specific requirements.
- Complete an approved plan of study consistent with the SIE Ph.D. Curriculum defined below
- Pass a comprehensive examination
- Present satisfactorily a dissertation proposal
- Present at least one colloquium
- Publish, or have under review, at least one scholarly paper in an archival journal, and publish at least one paper in conference proceedings
- Defend satisfactorily a dissertation.
The nominal sequencing and timing of the doctoral program requirements is as follows:
- Year 1
- Identify a Research Area
- Establish a working relationship with the faculty advisor
- Form an Advisory Committee
- Develop and submit a Plan of Study
- Year 2
- Finish taking courses
- Take Comprehensive Examination
- Develop a Plan of Research
- Present Dissertation Proposal
- Petition for Admission to Candidacy
- Year 3
- Present Colloquium
- Submit a paper for Publication
- Defend Dissertation
SIE PhD Curriculum
Mandatory Courses
SYS 6001 – Introduction to Systems Analysis and Design (1 course)
SYS 7096 – Systems Engineering Doctoral Colloquium (2 semesters as SIE doctoral student)
Foundations (3 courses selected from the following)
SYS 60XX – Autonomy and Controls I
SYS 60XX – Human Factors I
SYS 6003 – Optimization Models and Methods I
SYS 6005 – Stochastic Modeling I
SYS 6021 – Statistical Modeling I
Methodological Areas (5 courses from at least 2 areas)
Certain courses are listed in multiple areas. In cases where a course is listed in multiple areas, the student must decide which area the course satisfies for the student’s plan of study. Each course may only satisfy one area for the student’s plan of study. Other appropriate courses – as approved by the graduate committee in advance of registration – may be substituted into these areas.
Optimization
SYS 6042 – Network and Combinatorial Optimization
SYS 7063 – Simulation Optimization
Autonomy & Controls
APMA 6548 – Introduction to Chaos, Bifurcation, and Stability
ECE 7856 – Nonlinear Control Systems
ECE 8825 – Adaptive Control
SYS 60XX – Autonomous Mobile Robotics
SYS 60XX – Collaborative Autonomy
SYS 60XX – Reinforcement Learning
SYS 6014 – Stochastic Control and Decision Analysis
SYS 7005 – Stochastic Processes, Autonomy, and Controls
Statistical Modeling
STAT 5170 – Applied Time Series
STAT 6440 – Introduction to Bayesian Methods
SYS 6016 – Machine Learning
SYS 6018 – Data Mining
SYS 7063 – Simulation Optimization
Human Factors
SYS 60XX – Design of Experiments
SYS 60XX – Human Factors Design for Community Health
SYS 60XX – User Experience Design
SYS 6023 – Cognitive Engineering
SYS 6026 – Quantitative Models of Human Perceptual Information Processing
SYS 6064 – Applied Human Factors Engineering
Decision and Risk Analysis
SYS 6014 – Stochastic Control and Decision Analysis
SYS 6034 – Discrete-Event Stochastic Simulation
SYS 6035 – Agent-Based Modeling and Simulation
SYS 6041 – Ethics in Engineering Research and Practice
SYS 6050 – Risk Analysis
SYS 6070 – Environmental Systems Processes
SYS 7001 – Systems and Decision Science
SYS 7075 – Bayesian Forecast-Decision Theory
Note: Courses marked XX are currently offered as special topics courses and are planned to be made official courses within the year.
Research Electives (3 courses)
Courses at the 6000 and 7000 levels are chosen in consultation with the advisory committee to support the student’s research program.
Provisional Plan of Study based on Prior Coursework
Courses taken as part of previous graduate work may help to fulfill the above requirements. Any student wishing to receive such credit must petition the SIE graduate studies committee. In all cases at least 4 courses must be taken within the SIE graduate offerings, with the restriction that independent study courses and courses originating in other departments and cross-listed with SIE are not eligible.
In the summer before matriculation, each entering graduate student will be assigned a provisional plan of study based on the above requirements. This provisional plan will govern the selection of courses until such time as it is superseded by a plan of study developed by the student’s advisory committee. Thus, it is in the interest of the student to form the advisory committee expeditiously and thereby move to a plan of study tailored to support the student’s personal research objectives.
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