Earn Your Ph.D. in Modeling
and Simulation

Earn Your Ph.D. in Modeling and Simulation

The Ph.D. program requires a minimum of 72 credit hours of course work, including a minimum of 15 dissertation hours. The core consists of five required courses (15 credit hours) that provide an interdisciplinary framework for all students. The remaining 42 credit hours may consist of additional elective courses and research hours. Students are also expected to produce refereed publications as part of their doctoral studies. At least 27 hours of the total program must consist of formal course work, exclusive of independent study.

2023-2024 Application Deadlines

Applicants who plan to enroll full time in a degree program and who wish to be considered for university fellowships or assistantships should apply by January 15 (or earlier if your program has a deadline prior to January 15).

Domestic Application Deadline

Spring: November 1
Summer:
Fall: July 1

International Application Deadline

Spring: July 1
Summer:
Fall: January 15

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Courses and Milestones

Core Courses | 15 credit hours

  • COT6571 – Mathematical Foundations of Modeling and Simulation (3)
  • IDS6147 – Perspectives on Modeling and Simulation (3)
  • IDS6145 – Simulation Techniques (3)
  • IDS6262 – Research Design for Modeling and Simulation (3)
  • IDS6267 – Understanding Humans for Modeling and Simulation (3)

Restricted Electives | 3 credit hours

Students are required to take at least 3 credits (one class) of electives offered by SMST:

SMST Electives
  • IDC5602 – Cybersecurity: A Multidisciplinary Approach (3)
  • IDC6601 – Behavioral Aspects of Cybersecurity (3)
  • IDC6700 – Interdisciplinary Approach to Data Visualization (3)
  • IDS5142 – Modeling and Simulation for Instructional Design (3)
  • IDS 6740 – Nonlinear Dynamics
  • IDS6916 – Simulation Research Methods and Practicum (3)

Unrestricted Electives | 39 credit hours

All modeling and simulation Ph.D. students must take at least 39 credits of unrestricted elective courses that reflect their two areas of specialization. Students are expected to carefully select electives with guidance from the program director and/or their faculty adviser.

SMST has already identified many courses that students may choose as unrestricted electives. This list is displayed below. New courses are developed at the university every semester, so this list is updated once each year. Because new courses are added to the graduate catalog all the time, students may request program approval and inclusion for a course that benefits their area of study but is not on this list.

Unrestricted electives must consist of at least 9 credit hours of formal courses, excluding independent study. The remaining credits may consist of additional coursework, directed research, independent study and internship, as advised appropriately by the student’s faculty adviser and/or the program director.

Modeling and simulation Ph.D. Elective Courses

Previously approved unrestricted elective courses can be in various areas of focus or specialization. Course groupings are guides that are intended to assist with advising and selection of courses so that students can meet educational goals and objectives. They are not exhaustive. Nor are they intended to restrict elective choices within focus areas. We strongly encourage modeling and simulation students to maintain an interdisciplinary approach to their graduate studies.

If a student identifies a UCF course that may be of value to a M&S research area but the course is not identified in one of the below lists, the student may request approval from the graduate program director for the course to be used as an elective in the Graduate Plan of Study. All requests must be made in advance of enrolling in the course.

Electives categorized as “General” and “Fundamentals of Modeling and Simulation” are appropriate for all students regardless of interest area. The remaining categories are grouped by area of interest.

General Electives Including Credit Hours

  • ESI 6247 – Experimental Design and Taguchi Methods (3)
  • ESI 6891 – IEMS Research Methods (3)
  • IDS 5907 – Independent Study (Variable)
  • IDS 5917 – Directed Research (Variable)
  • IDS 6908 – Independent Study (Variable)
  • IDS 6918 – Directed Research (Variable)
  • IDS 6946 – Internship (Variable)
  • IDS 7919 – Doctoral Research (Variable)
  • PHI 5340 – Research Methods in the Cognitive Sciences (3)
  • PSY 6216C – Research Methodology (4)
  • STA 5205 – Experimental Design (3)

Fundamentals of Modeling and Simulation

  • ESI 5219 – Engineering Statistics (3)
  • ESI 6217 – Statistical Aspects of Digital Simulation (3)
  • ESI 6247 – Experimental Design and Taguchi Methods (3)
  • ESI 6532 – Object-Oriented Simulation (3)
  • IDC 6700 – Interdisciplinary Approach to Data Visualization (3)
  • IDS 6146 – Modeling and Simulation Systems (3)
  • IDS 6149 – Modeling and Simulation for Test and Evaluation (3)
  • IDS 6950 – Modeling and Simulation Capstone Report Planning (1)

Behavioral Cybersecurity Electives

  • CAP 6133 – Advanced Topics in Computer Security and Computer Forensics (3)
  • CAP 6135 – Malware and Software Vulnerability Analysis (3)
  • CDA 6530 – Performance Models of Computers and Networks (3)
  • CJE 6688 – Cyber Crime and Criminal Justice (3)
  • CNT 5008 – Computer Communication Networks Architecture (3)
  • CNT 5410L – Cyber Operations Lab (3)
  • CNT 6519 – Wireless Security and Forensics (3)
  • COT 5405 – Design and Analysis of Algorithms (3)
  • EEL 6785 – Computer Network Design (3)
  • EEL 6883 – Software Engineering II (3)
  • ESI 5531 – Discrete Systems Simulation (3)
  • EXP 5256 – Human Factors I (3)
  • EXP 6506 – Human Cognition and Learning (3)
  • IDC 5602 – Cybersecurity: A Multidisciplinary Approach (3)
  • IDC 6600 – Emerging Cyber Issues (3)
  • IDC 6601 – Behavioral Aspects of Cybersecurity (3)
  • IDS 6916 – Simulation Research Methods and Practicum (3)
  • INR 6365 – Seminar on Intelligence (3)
  • INR 6366 – The Intelligence Community (3)
  • PHI 6938 – ST: Digital Ethics (3)
  • STA 5703 – Data Mining Methodology I (3)
  • STA 5825 – Stochastic Processes and Applied Probability Theory (3)

Human Systems Electives 

  • CAP 6515 – Algorithms in Computational Biology (3)
  • CAP 6671 – Intelligent Systems: Robots, Agents, and Humans (3)
  • CAP 6676 – Knowledge Representation (3)
  • DIG 6432 – Transmedia Story Creation (3)
  • DIG 6812 – Digital Interaction for Informal Learning (3)
  • EIN 5248 – Ergonomics (3)
  • EIN 5317 – Training System Design (3)
  • EIN 6215 – System Safety Engineering and Management (3)
  • EIN 6258 – Human Computer Interaction (3)
  • EIN 6649C – Intelligent Tutoring Training System Design (3)
  • EME 6458 – Virtual Teaching and the Digital Educator (3)
  • EME 6507 – Multimedia for Education and Training (3)
  • EME 6601 – Instructional Simulation Design for Training and Education (3)
  • EME 6614 – Instructional Game Design for Training and Education (3)
  • EXP 5208 – Sensation and Perception (3)
  • EXP 5256 – Human Factors I (3)
  • EXP 6255 – Human Performance (3)
  • EXP 6257 – Human Factors II (3)
  • EXP 6258 – Human Factors III (3)
  • EXP 6506 – Human Cognition and Learning (3)
  • EXP 6541 – Advanced Human Computer Interaction (3)
  • IDS 6148 – Human Systems Integration for Modeling and Simulation (3)
  • IDS 6149 – Modeling and Simulation for Test and Evaluation (3)
  • PHI 5225 – Philosophy of Language (3)
  • PHI 5325 – Topics in Philosophy of Mind (3)
  • PHI 5327 – Topics in the Cognitive Sciences (3)
  • PHI 5329 – Philosophy of Neuroscience (3)
  • PSB 5005 – Physiological Psychology (3)
  • TTE 6270 – Intelligent Transportation Systems (3)

Computer Visualization Electives

  • CAP 5725 – Computer Graphics I (3)
  • CAP 6411 – Computer Vision Systems (3)
  • CAP 6412 – Advanced Computer Vision (3)
  • CAP 6676 – Knowledge Representation (3)
  • CDA 5106 – Advanced Computer Architecture (3)
  • COT 5405 – Design and Analysis of Algorithms (3)
  • DIG 6605 – Physical Computing (3)
  • DIG 6647 – History and Theory of Dynamic Media (3)
  • EIN 6258 – Human Computer Interaction (3)
  • EEL 5173 – Linear Systems Theory (3)
  • EEL 5771C – Engineering Applications of Computer Graphics (3)
  • EEL 5820 – Image Processing (3)
  • EEL 5825 – Pattern Recognition and Learning from Big Data (3)
  • EEL 5874 – Expert Systems and Knowledge Engineering (3)
  • EEL 6823 – Image Processing II (3)
  • EEL 6843 – Machine Perception 3 (3)
  • ESI 6247 – Experimental Design and Taguchi Methods (3)
  • MAP 5117 – Mathematical Modeling (3)
  • MAP 6118 – Introduction to Nonlinear Dynamics (3)
  • MAT 5712 – Scientific Computing (3)

Quantitative Methods for Simulation, Modeling and Analysis

  • CAP 5512 – Evolutionary Computation (3)
  • CAP 6515 – Algorithms in Computational Biology (3)
  • CDA 6530 – Performance Models of Computers and Networks (3)
  • COT 5405 – Design and Analysis of Algorithms (3)
  • EEL 5173 – Linear Systems Theory (3)
  • EEL 6878 – Modeling and Artificial Intelligence (3)
  • EIN 6528 – Simulation Based Life Cycle Engineering (3)
  • ESI 5306 – Operations Research (3)
  • ESI 5531 – Discrete Systems Simulation (3)
  • ESI 6217 – Statistical Aspects of Digital Simulation (3)
  • ESI 6247 – Experimental Design and Taguchi Methods (3)
  • IDC 6700 – Interdisciplinary Approach to Data Visualization (3)
  • MAP 5117 – Mathematical Modeling (3)
  • MAP 6111 – Mathematical Statistics (3)
  • MAP 6118 – Introduction to Nonlinear Dynamics (3)
  • MAP 6207 – Optimization Theory (3)
  • MAP 6385 – Applied Numerical Mathematics (3)
  • MAP 6407 – Integral Equations and the Calculus of Variations (3)
  • MAP 6408 – Perturbations and Asymptotic Methods (3)
  • MAP 6445 – Approximation Techniques (3)
  • MAT 5712 – Scientific Computing (3)
  • STA 5703 – Data Mining Methodology I (3)
  • STA 5825 – Stochastic Processes and Applied Probability Theory (3)
  • STA 6236 – Regression Analysis (3)
  • STA 6246 – Linear Models (3)
  • STA 6326 – Theoretical Statistics I (3)
  • STA 6327 – Theoretical Statistics II (3)
  • STA 6329 – Statistical Applications of Matrix Algebra (3)
  • STA 6704 – Data Mining Methodology II (3)
  • STA 6714 – Data Preparation (3)

Simulation in Healthcare Electives

  • CAP 6515 – Algorithms in Computational Biology (3)
  • CAP 6671 – Intelligent Systems: Robots, Agents, and Humans (3)
  • CAP 6676 – Knowledge Representation (3)
  • DIG 6647 – History and Theory of Dynamic Media (3)
  • DIG 6812 – Digital Interaction for Informal Learning (3)
  • EEL 5820 – Image Processing (3)
  • EEL 6823 – Image Processing II (3)
  • EIN 6645 – Real-Time Simulation Agents (3)
  • HUM 5802 – Applied Contemporary Humanities (3)
  • NGR 6717 – Introduction to Healthcare Simulation (3)
  • NGR 6771L – Healthcare Simulation Practicum (Variable)
  • NGR 6794 – Organizational Leadership and Operations in Healthcare Simulation (3)
  • NGR 6978 – Healthcare Simulation Capstone Project (3)
  • PHI 5329 – Philosophy of Neuroscience (3)
  • PSB 5005 – Physiological Psychology (3)
  • SPA 6417 – Cognitive/Communicative Disorders (3)
  • CAP 5512 – Evolutionary Computation (3)
  • CAP 5610 – Machine Learning (3)
  • CAP 5636 – Advanced Artificial Intelligence (3)
  • CAP 6671 – Intelligent Systems: Robots, Agents, and Humans (3)
  • CAP 6676 – Knowledge Representation (3)
  • DIG 6812 – Digital Interaction for Informal Learning (3)
  • EEL 5771C – Engineering Applications of Computer Graphics 3 (3)
  • EEL 5874 – Expert Systems and Knowledge Engineering (3)
  • EEL 6878 – Modeling and Artificial Intelligence (3)
  • EIN 5251 – Usability Engineering (3)
  • EIN 5255C – Interactive Simulation (3)
  • EIN 6258 – Human Computer Interaction (3)
  • EIN 6645 – Real-Time Simulation Agents (3)
  • EIN 6647 – Intelligent Simulation (3)
  • EIN 6649C – Intelligent Tutoring Training System Design (3)
  • EME 6613 – Instructional System Design (3)
  • ESI 6247 – Experimental Design and Taguchi Methods (3)
  • IDS 6149 – Modeling and Simulation for Test and Evaluation (3)

Simulation Infrastructure Electives

  • CAP 6671 – Intelligent Systems: Robots, Agents, and Humans (3)
  • CAP 6676 – Knowledge Representation (3)
  • CDA 5106 – Advanced Computer Architecture (3)
  • CDA 6107 – Parallel Computer Architecture (3)
  • CDA 6530 – Performance Models of Computers and Networks (3)
  • CNT 5008 – Computer Communication Networks Architecture (3)
  • COT 5405 – Design and Analysis of Algorithms (3)
  • DIG 6605 – Physical Computing (3)
  • EEL 5173 – Linear Systems Theory (3)
  • EEL 6762 – Performance Analysis of Computer and Communication Systems (3)
  • EEL 6785 – Computer Network Design (3)
  • EEL 6878 – Modeling and Artificial Intelligence (3)
  • EEL 6883 – Software Engineering II (3)
  • ESI 6551 – Systems Engineering (3)
  • MAT 5712 – Scientific Computing (3)

Simulation Management Electives

  • EIN 5108 – The Environment of Technical Organizations (3)
  • EIN 5117 – Management Information Systems I (3)
  • EN 5140 – Project Engineering (3)
  • EIN 5356 – Cost Engineering (3)
  • EIN 6182 – Engineering Management (3)
  • EIN 6215 – System Safety Engineering and Management (3)
  • EIN 6339 – Operations Engineering (3)
  • EIN 6357 – Advanced Engineering Economic Analysis (3)
  • EIN 6528 – Simulation Based Life Cycle Engineering (3)
  • ESI 5227 – Total Quality Improvement (3)
  • ESI 6224 – Quality Management (3)
  • ESI 6358 – Decision Analysis (3)
  • ESI 6551 – Systems Engineering IDS 6149 – Modeling and Simulation for Test and Evaluation (3)

Applying Previously Earned Graduate Coursework

Students may opt to apply up to 30 credits from a previously earned graduate degree or certificate to their plan of study. The university has specific regulations about which credits can be attributed to the student’s degree program. Some of these requirements include grade earned, topic, type of term (whether semester, quarter, etc.) and whether the course was used towards another academic plan. Each course must be evaluated individually to determine if the rigor of the course is equivalent to or greater than the standard set forth by UCF. Credits earned through individualized instruction (e.g., independent study, directed research, thesis, etc.) cannot be used toward the student’s program as they cannot be evaluated for equivalency to UCF work. Students who wish to apply previously earned graduate coursework to their degree program are encouraged to collect syllabi for all of their courses (or from a representative term), as well as consult with the Modeling and Simulation Graduate Program director regarding eligibility. Detailed information about the university’s transfer policy can be found in the graduate catalog.

Dissertation | Minimum of 15 Credit Hours

Before students enter the dissertation phase of their degree programs, they must successfully complete all of the following milestones (detailed information is available in program handbook).

Milestones

Milestone 1 – Admission to Ph.D. Program

Administrative Requirements

  • Plan of Study submitted to program
  • Collaborative Institutional Training Initiative (CITI) training
  • 4 Responsible Conduct of Research (RCR) workshops: 2 required, 2 elective

Curriculum Requirements

Core Classes

Milestone 2 – Qualifying Exam

Administrative Requirements

  • Build candidacy (dissertation) committee
  • Submit dissertation research to Institutional Review Board (IRB) for approval or exemption
  • Start submitting research for publication

Curriculum Requirements

Elective Classes

Milestone 3 – Candidacy Examination

Administrative Requirements

  • Format Review
  • Defense Announcement
  • Final Defense of Dissertation
  • 2 publications completed by final defense

Curriculum Requirements

Dissertation Enrollment (IDS7980)

Milestone 4 – Submission of Dissertation to University