decision support. Visualization of these is also a significant part of these Department of areas. Collaborative Autonomous Laboratory Computational Modeling The Collaborative Autonomous Systems Laboratory supports instructional and multidisciplinary activities related to autonomous systems. and This forth laboratory area is shared with the mechanical and aerospace department. CMSE maintains 4 PC workstations and 10 various types of robotic systems. The lab contains an area dedicated to cyber security research as related to collaborative autonomous systems. Web Site: http://www.odu.edu/cmsv (http://www.odu.edu/cmsv/) The CAVE (CAVE Automated Virtual Environment) 1300 Engineering and Computational Sciences Building The CAVE (Cave Automated Virtual Environment) Virtual Reality 757-683-3720 laboratory area contains several 3D visualization systems. The CAVE is Yuzhong Shen, Chair a high-resolution projection-screen virtual reality . The screens are Masha Sosonkina, Graduate Program Director arranged in a 10 foot cube with computer-generated images projected on three walls and a floor. The CAVE lab also contains a 3 meter Vision Dome Department Description projection system and an Immersa-Desk virtual reality display. Two 3D printers are also placed in the CAVE Lab. The CMSE Department offers an undergraduate four-year degree program leading to the Bachelor of Science in Modeling and Simulation Engineering Associated Centers: (BS-M&SE). The department also offers programs of graduate study leading to the degrees , Master of Science, A significant resource to the department is the Virginia Modeling, Analysis of Engineering, and with a major in Modeling and and Simulation Center located adjacent to the 's Tri-Cities Higher Simulation. The department's academic programs are coupled with a strong Education Center in Suffolk, Virginia. VMASC occupies a two-story department research program conducted jointly with researchers from the 60,000 square foot building designed to support state-of-the-art research Virginia Modeling, Analysis and Simulation Center (VMASC). Research in modeling, simulation and visualization. Some of the center's facilities activities range from investigation of fundamental modeling and simulation are used in the department's educational programs; in addition, VMASC methods and technologies to applications of modeling and simulation in the researchers teach courses and mentor students in the department's academic domains of medicine and health care, transportation, education and gaming, programs. science and engineering, homeland security and defense, and business enterprise decision support. List of Degrees and Certificates • Master of Science, Engineering - Modeling and Simulation Special Facilities: • - Modeling and Simulation The CMSE Department is located on the first floor of the E. V. Williams • Doctor of Philosophy, Engineering - Modeling and Simulation Engineering and Computational Sciences Building on the Old Dominion • in Modeling and Simulation Engineering University Norfolk Campus. In addition to the department and faculty offices, this facility also houses several instructional and research • Advanced Engineering Certificate in Cyber Systems Security laboratories, a virtual reality theater, and a four-walled C.A.V.E. (Cave Automatic Virtual Environment). Master of Science, Engineering - Modeling Undergraduate Projects and Research Laboratory and Simulation The master's degree in modeling and simulation (M&S) emphasizes a strong, The Undergraduate Projects and Research Laboratory, is mainly used for common subject core while providing the student with the flexibility to facilitating modeling and simulation projects-based instruction in both design a plan of study to meet each individual's study objectives and needs. lower and upper division undergraduate levels. This also involves courses The purpose of the program's subject core is to provide a common academic in the major with a significant laboratory component. The Laboratory can foundation for all simulation students. Thus, all students in this program accommodate 24 students with laptop computers and provide 5 workstations will have grounding in the same methods, principles, and philosophy of for undergraduate labs and research. Each workstation contains a high simulation. This provides the mechanisms for the simulationist to work performance computer and collaboration spaces. The lab also contains a across disciplines and domains while maintaining a common frame of Polycom Teleconference system to support distance learning. The lab is reference for communication, technical specialization, and advanced study equipped with 3 digital projectors to support teaching. and research. The Master of Science (MS) in Modeling and Simulation Medical Laboratory offers two options: Option and Course Option. The Thesis Option requires six hours of thesis credit and 24 hours of course credit and it is The Medical Simulations Laboratory is mainly used to support teaching directed primarily at full-time students who are preparing for a career and research activities related to medical simulations for planning, training, in advanced M&S research and/or academic positions. The Course education, analysis and visualization. It contains 15 high performance PC Option requires 30 hours of course credit and it is focused on developing workstations, 4 haptic devices, three 3D scanners, two 3D printers, 4 reach- the practical skills and knowledge needed to solve problems requiring in displays, 3 LCD TVs, 6 Oculus Rift headsets, 2 HTC Vive headsets, and 2 applications of modeling and simulation. The Course Option is further Microsoft Hololens. The laboratory is also equipped with a large selection of divided into two tracks: Development Track and Application Track. The software such as Autodesk Maya, Google SketchUp, Microsoft XNA Game Development Track is programming intensive and prepares students for Studio, Unity Game Engine, and ArcGIS. advanced simulation development, while the Application Track focuses on Applied M&S Research Laboratory the usage of existing advanced simulation tools. The Applied M&S Research Laboratory is the third laboratory area. This The program's subject core consists of: graduate research laboratory contains PC workstations and spaces for 10 1. an overview of modeling and simulation; graduate students and also supports faculty/VMASC collaborative research 2. an in-depth exploration of specific simulation methodological activities. Several research topics are conducted in this laboratory including approaches; high performance computing, cyber security, simulation architectures, transportation systems, military M&S, digital manufacturing, and enterprise 3. simulation system modeling principles and techniques;

1 Department of Computational Modeling and Simulation Engineering 4. an introduction to computer visualization and visual simulation; and, MSIM 725 Principles of Combat Modeling and 5. principles of stochastic analysis. Simulation MSIM 742 Synthetic Environments Most courses are offered in distance learning format. They are delivered to 's centers and are available MSIM 776 Simulation Modeling in Transportation synchronously using video teleconferencing software. Networks Other courses with graduate program director's approval. Master of Science Admission Requirements The remaining course credits (12 credits for the thesis option and 18 credits The Master’s Degree in Modeling and Simulation is designed for students for the course option) are elective course credits. These courses are selected having bachelor’s degrees in Engineering, Science or Mathematics, although to achieve one or more program objectives or themes and must be approved students from other educational backgrounds may apply with appropriate by the student's advisor and/or graduate program director. Elective courses leveling courses. Prerequisites for admission include: mathematics – two outside the CMSE Department must be approved by the graduate program courses in differential and integral calculus and one course in calculus- director. The thesis option concludes with 6 credit hours of thesis credit based probability and statistics; and computer science – algorithmic problem (MSIM 699) and a thesis defense and the course option concludes with a solving using a high-level object-oriented programming language such as C comprehensive exam. Students must also complete the Responsible Conduct ++. of Research for Engineers training online. A minimum GPA of 2.80 overall and a minimum GPA of 3.0 in the Certain students will need to take pre-requisite leveling courses that will undergraduate major are required. Students with notable deficiencies count towards the 12 credit hour elective course requirement. These courses may be considered for provisional admission and will be required to are: MSIM 510 Model Engineering; MSIM 541 Computer Graphics and complete prerequisite course requirements in addition to the graduate degree Visualization; MSIM 602 Simulation Fundamentals; and, MSIM 603 requirements. Job experience and training may be considered in evaluating Simulation Design. The Course Option Application Track only requires prerequisite requirements. MSIM 510 Model Engineering and MSIM 602 Simulation Fundamentals as Applicants should plan to submit a completed application form, transcripts leveling courses. from all colleges and attended, GRE scores (verbal, quantitative, The MS Course Option is also offered online via the Blackboard Academic and analytical writing - required of MS applicants for the thesis option Suite and WebEx that provides online lectures, homework submissions, only), a resume and personal statement of objectives, two letters of examinations, discussion boards, wikis, video/audio collaboration sessions recommendation from former university instructors or current employer and grading. Students having access to reliable high speed internet (recommendation letters are required of MS applicants for the thesis option service can connect and participate in engaging discussion and distributed only), and TOEFL scores if an international applicant. asynchronous learning with the instructor and other students. All course Potential prerequisite courses for the master’s degrees in modeling and materials are distributed and collected electronically. Students located in the simulation include the following: Hampton Roads region may utilize live courses to fulfill the elective course requirement with approval from the CMSE graduate program director. 1. Introductory differential and integral calculus equivalent to MATH 211 (Calculus I) and MATH 212 (Calculus II). Doctor of Engineering - Modeling and 2. Calculus-based probability and statistics; this material is available for Simulation graduate credit in PSYC 727. Undergraduate courses STAT 330 or ENMA 420 will also meet the prerequisite requirement. The D. Eng. in Modeling and Simulation program focuses on developing the 3. Computer science fundamentals including an object-oriented advanced skills and knowledge to enable the graduate to conduct and lead programming language such as C++, algorithmic problem solving, and advanced technical M&S projects in an engineering environment. It affords data structures. engineering practitioners the opportunity to achieve advanced graduate education beyond the master’s degree. Master of Science Degree Requirements For complete information on admission requirements and The Master of Science program requires 12 hours of course credit in core degree requirements, please refer to the Doctor of modeling and simulation foundation courses. These foundation courses Engineering program information at: http://catalog.odu.edu/ include: graduate/frankbattencollegeofengineeringandtechnology/ #doctorofengineeringprogram MSIM 741 Principles of Visualization 3 MSIM 551 Analysis for Modeling and Simulation 3 The program of study for the D.Eng. in M&S program is developed or MSIM 751 Advanced Analysis for Modeling and Simulation with the approval of the graduate program director and the student’s advisor. The program shall include a minimum of Advanced Modeling Course (see list below) 3 18 credits of professional course work (http://catalog.odu.edu/ Advanced Simulation Course (see list below) 3 graduate/frankbattencollegeofengineeringandtechnology/ #doctorofengineeringprogram). The course ENGN 812 Engineering Advanced Modeling Course Examples (3 credits) Leadership is cross-listed with the course ENMA 880 Leadership for MSIM 607 Machine Learning I Engineering Managers and ENGN 612 Analysis of Organizational Systems MSIM 660 System Architecture and Modeling is cross-listed with ENMA 601 Analysis of Organizational Systems. Other professional courses can be substituted by other courses approved by the MSIM 702 Systemic Decision Making Graduate Program Director if these professional courses are not available. MSIM 730 Simulation Formalisms MSIM 772 Modeling Global Events The D.Eng. also requires 18 credits of technical core course work beyond the master’s degree distributed as follows: MSIM 774 Transportation Network Flow Models Other courses with graduate program director's approval. Technical Core Courses 18 Advanced Simulation Course from the list below Advanced Simulation Course Examples (3 credits) MSIM 830 Simulation Formalisms MSIM 711 Finite Element Analysis MSIM 842 Synthetic Environments MSIM 722 Cluster Parallel Computing

Department of Computational Modeling and Simulation Engineering 2 MSIM 851 Advanced Analysis for Modeling and 3. Knowledge of the content of the foundation courses required in the Simulation Modeling and Simulation Master’s Program. Two approved technical elective courses - 6 credits Doctor of Philosophy Degree Requirements Advanced Simulation Course Examples (3 credits) The Ph.D. in modeling and simulation is offered in accordance with the general requirements for doctoral degrees as specified in the Requirements MSIM 811 Finite Element Analysis for Graduate Degrees Section of this Catalog. Specific program of study MSIM 822 Cluster Parallel Computing requirements for the concentration in modeling and simulation include the MSIM 825 Principles of Combat Modeling and following: Simulation 1. Completion of a minimum of 24 credits of course work beyond the MSIM 876 Simulation Modeling in Transportation master’s degree; and a minimum of 24 credits of dissertation research. Networks 2. Successful completion of a written diagnostic examination before Other courses with graduate program director's approval. completion of nine credits of advanced course work. No more than three credits from course work satisfying foundation 3. Successful completion of a written and oral qualifying (candidacy) knowledge requirements may be included in the program of study for examination near the completion of the course work. technical elective credit. At least three-fifths of the non-project coursework 4. Successful presentation of a dissertation research proposal at the must be at the 800-level. beginning of the dissertation research. Certain students entering the program will be required to complete additional 5. The successful completion and public defense of a dissertation pre-requisite leveling courses. These courses are: MSIM 510 Model representing independent, original research worthy of publication in a Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 peer-reviewed scholarly journal. Simulation Fundamentals; and MSIM 603 Simulation Design. The program of study for the Ph.D. in M&S program is developed with the For graduation, students must complete the requirements for their final approval of the graduate program director and the student’s advisor. The project and the Responsible Conduct of Research for Engineers training program shall include a minimum of 24 credit hours of course work beyond online. the master’s degree distributed as follows. Doctor of Philosophy, Engineering - Common Core Modeling and Simulation Advanced Simulation Course (see the list below) 3 MSIM 830 Simulation Formalisms 3 The Ph.D. in Modeling and Simulation program focuses on developing MSIM 842 Synthetic Environments 3 the necessary skills and knowledge to enable the graduate to conduct and evaluate independent, original research in an area of modeling and MSIM 851 Advanced Analysis for Modeling and 3 simulation. The goal of the program is to prepare students for careers in Simulation teaching and research at academic institutions, as well as the conduct or Total Hours 12 leadership of research and development in public and private organizations. Advanced Simulation Course Examples (3 credits) Doctor of Philosophy Admission Requirements MSIM 811 Finite Element Analysis Admission to the Ph.D. in M&S program is made in accordance with Old MSIM 822 Cluster Parallel Computing Dominion University and Batten College of Engineering and Technology requirements for doctoral programs as specified in this Catalog. Specific MSIM 825 Principles of Combat Modeling and requirements for the modeling and simulation degree include the following: Simulation MSIM 876 Simulation Modeling in Transportation 1. Completion of a master’s degree in an appropriate and closely related Networks field is expected. However, students who have completed 24 credits of Other courses with graduate program director's approval. graduate courses in an appropriate field from an accredited institution may apply. Electives - Minimum of 12 credits of elective courses that provide a 2. A minimum GPA in graduate course work of 3.50 (out of 4.0) is basis for dissertation research. No more than six credits from course work required of most students. A student with a GPA greater than 3.25 and satisfying foundation knowledge requirements may be included in the with evidence of a high level of professional capability in the field of program of study for elective credit. At least three-fifths (15 credits) of non- modeling and simulation may be eligible for admission to the program dissertation course work must be at the 800-level. Elective courses outside upon submission of a petition to the graduate program director. the MSVE Department must be approved by the graduate program director. 3. Recent scores (typically, not more than five years old) on the Graduate Certain students entering the program will be required to complete additional Record Examination’s (GRE) verbal, quantitative, and analytical writing pre-requisite leveling courses. These courses are: MSIM 510 Model sections must be submitted by all applicants. Engineering; MSIM 541 Computer Graphics and Visualization; MSIM 602 4. Three letters of recommendation (typically at least two of which Simulation Fundamentals; and MSIM 603 Simulation Design. are from faculty in the highest degree program completed when the application is within five years of graduation from that degree program) For graduation, students must successfully defend their dissertation and are required. complete the Responsible Conduct of Research for Engineers training 5. The applicant must submit a statement of purpose, goals, and objectives online. related to the program and a resume. Graduate Certificate in Modeling and Applicants are expected to have the following foundation knowledge: Simulation Engineering 1. Mathematics fundamentals including differential and integral calculus, The Graduate Certificate in Modeling and Simulation Engineering is ordinary differential equations, calculus-based probability and statistics, designed for those who meet the admission requirements of the modeling and linear algebra. and simulation master's program and wish to broaden their knowledge of 2. Computer science fundamentals including an object-oriented modeling and simulation related principles and practices without pursuing programming language such as C++, algorithmic problem solving, and a graduate degree. This is a 12 credit hour non-degree program offered by data structures. the Department of Computational Modeling & Simulation Engineering. The 3 Department of Computational Modeling and Simulation Engineering certificate program is open to both degree-seeking and non-degree-seeking Certificate Program Admission Requirements graduate students. Certain courses taken for the certificate program may later All applicants admitted to the certificate program must have earned a be applied to the master’s degree in modeling and simulation. baccalaureate degree in engineering, mathematics, science, or a related Graduate Certificate Admission Requirements STEM field from a regionally-accredited institution or an equivalent degree from a foreign institution. Those whose native language is not English must Students should have either an from a regionally submit a minimum score of 230 on the computer-based TOEFL or 80 on the accredited institution and should have a mathematical background TOEFL iBT. through calculus, along with a calculus based probability and statistics course. Students should submit a graduate non-degree application through Certificate Program Curriculum Requirements the Office of Admissions, and then submit a departmental application with The Graduate Certificate in Cyber Security requires completion of 12 credit copies of unofficial transcripts from all previous coursework to the CMSE hours of graduate course work, consisting of two core courses and two Department. Departmental applications are available online on the CMSE elective courses from the course list below. Department’s website – https://www.odu.edu/cmse (https://www.odu.edu/ cmse/) - and should be sent to: Required Core Courses MSIM 570 Foundations of Cyber Security 3 Academic Advisor and Program Manager CMSE Department MSIM/ENMA 670 Cyber 3 Old Dominion University Electives (Select two of the following): 6 1300 Engineering and Computational Sciences Building ECE 516 Cyber Defense Fundamentals Norfolk, VA 23529 ECE 519 Cyber Physical System Security Graduate Certificate Course Requirements MSIM 673 Threat Modeling and Risk Analysis The Graduate Certificate in Modeling and Simulation Engineering Total Hours 12 requires the completion of 12 credit hours at the graduate level. The course requirements are: MODELING AND SIMULATION Courses MSIM 506. Introduction to Distributed Simulation. 3 Credits. Select three courses from the following: 9 An introduction to distributed simulation. Topics include motivation MSIM 601 Introduction to Modeling and Simulation for using distributed simulation, distributed simulation architectures, MSIM 602 Simulation Fundamentals time management issues, and distributed simulation approaches. Current MSIM 510 Model Engineering standards for distributed simulation are presented. MSIM 603 Simulation Design MSIM 508. Introduction to Game Development. 3 Credits. MSIM 541 Computer Graphics and Visualization Requires an understanding of physics and either CS 361 or MSIM 331. An introductory course focused on game development theory and modern MSIM 551 Analysis for Modeling and Simulation practices with emphasis on educational game development. Topics include * MSIM Elective 3 game architecture, computer graphics theory, user interaction, audio, high Total Hours 12 level shading language, animation, physics, and artificial intelligence. The developed games can run on a variety of computer, mobile, and gaming * A graduate level elective approved by the Graduate platforms. Program Director. This elective may be an MSIM MSIM 510. Model Engineering. 3 Credits. course or from another discipline outside of modeling The goal of this course is to develop understanding of the various modeling and simulation. It is possible that this course may be paradigms appropriate for capturing system behavior and conducting digital outside of the discipline of modeling and simulation, but of many types of systems. The techniques and concepts approved because it complements the field of modeling discussed typically include UML, concept graphs, Bayesian nets, Markov and simulation and the student's interests. models, Petri nets, system dynamics, Bond graphs, etc. Students will report An overall GPA of 3.0 or better is required to earn the graduate certificate in on a particular technique and team to implement a chosen system model. modeling and simulation engineering. (cross-listed with ECE 510). MSIM 511. Networked System Security. 3 Credits. Advanced Engineering Certificate in Cyber Course presents an overview of theory, techniques and protocols that are Systems Security used to ensure that networks are able to defend themselves and the end- systems that use networks for data and information communication. Course The certificate program aims to provide a thorough understanding the cyber will also discuss industry-standard network security protocols at application, security threats faced by the stand-alone computer systems, networked socket, transport, network, VPN, and link layers, popular network security systems, IT infrastructure, and cyber physical systems having embedded tools, security, performance modeling and quantification and network computer systems operated by individuals, small businesses and large penetration testing. Discussion will be based on development of system level enterprises along with the knowledge required to defend against these models and simulations of networked systems. Cross-listed with ECE 511. threats. The course will enable participants to learn state of the art techniques necessary for analyzing cyber security risks, preventing, detecting and MSIM 516. Cyber Defense Fundamentals. 3 Credits. recovering from cyber attacks through class room instructions and hands-on This course focuses on cybersecurity theory, information protection and lab work. The program uniquely accommodates students from engineering, assurance, and computer systems and networks security. The objectives are math and sciences as well as practicing engineers and managers. The course to understand the basic security models and concepts, learn fundamental will make use of ODU's multidisciplinary strengths in the fields of Cyber knowledge and tools for building, analyzing, and attacking modern security Systems, Computer Engineering, Software Engineering and Modeling systems, and gain hands-on experience in cryptographic algorithms, security and Simulation. This program is designed both as a complement for fundamental principles, and Internet security protocol and standards. Cross- students working on graduate degrees and for those personnel working listed with ECE 516. on information and cyber systems used in industry, small businesses, healthcare, government, military and home land security. It is anticipated that students will complete the program in 2 semesters (full time enrollment) or 2 years (part-time enrollment or working to complement an existing graduate program).

Department of Computational Modeling and Simulation Engineering 4 MSIM 519. Cyber Physical Systems Security. 3 Credits. MSIM 580. Introduction to Artificial Intelligence. 3 Credits. Cyber Physical Systems (CPS) integrate computing, networking, and Introduction to concepts, principles, challenges, and research in major areas physical processes. The objectives of this course are to learn the basic of artificial intelligence. Areas of discussion include: natural language and concepts, technologies and applications of CPS, understand the fundamental vision processing, machine learning, machine logic and reasoning, robotics, CPS security challenges and national security impact, and gain hands-on expert and mundane systems. Laboratory work required. Prerequisite: experience in CPS infrastructures, critical vulnerabilities, and practical Instructor approval. countermeasures. Cross-listed with ECE 519. MSIM 595. Topics in Modeling and Simulation Engineering. 3 Credits. MSIM 540. Game Physics Modeling and Simulation. 3 Credits. Special topics of interest with emphasis placed on recent developments in This introductory class will provide the student with a basic understanding modeling and simulation engineering. of the mathematical foundations and algorithmic concepts needed to become MSIM 596. Topics in Modeling and Simulation Engineering. 1-3 competent at implementing game physics engines. We will emphasize Credits. the mathematical foundations that apply to many areas of simulation, Special topics of interest with emphasis placed on the recent developments which subsumes the mathematics of game physics, such as linear algebra in modeling and simulation engineering. Prerequisites: permission of the emphasizing vectors and matrices, as well as introductory vector calculus. instructor. This class will also exploit open-source C++ software implemented by the author of the textbook. Prerequisites: CS 250. MSIM 597. Independent Study in Modeling and Simulation Engineering. 3 Credits. MSIM 541. Computer Graphics and Visualization. 3 Credits. Individual analytical, computational, and/or experimental study in an area The course provides a practical treatment of computer graphics and selected by the student. Supervised and approved by the advisor. visualization with emphasis on modeling and simulation applications. It covers computer graphics fundamentals, visualization principles, and MSIM 601. Introduction to Modeling and Simulation. 3 Credits. software architecture for visualization in modeling and simulation. Pre- or Modeling and simulation (M&S) discipline surveyed at an overview level corequisites: CS 250 and MSIM 603. of detail. Basic terminology, modeling methods, and simulation paradigms are introduced. Applications of M&S in various disciplines are discussed. MSIM 551. Analysis for Modeling and Simulation. 3 Credits. The course provides a general conceptual framework for those interested An introduction to analysis techniques appropriate to the conduct of in using M&S and for further studies in M&S. Not open to MSVE degree modeling and simulation studies. Topics include input modeling, random seeking students. Prerequisites: graduate standing; undergraduate exposure number generation, output analysis, variance reduction techniques, and to calculus and probability & statistics. experimental design. In addition, techniques for verification & validation are introduced. Course concepts are applied to real systems and data. MSIM 602. Simulation Fundamentals. 3 Credits. Prerequisites: STAT 330. An introduction to the modeling and simulation discipline. Introduction to discrete event simulation (DES) including simulation methodology, MSIM 562. Introduction to Medical Image Analysis. 3 Credits. input data modeling, output data analysis, and an overview of DES Introduction to basic concepts in medical image analysis. Medical image tools. Introduction to continuous simulation (CS) including simulation registration, segmentation, feature extraction, and classification are methodology, differential equation models, numerical solution techniques, discussed. Basic psychophysics, fundamental ROC analysis and FROC and an overview of CS tools. Prerequisites: graduate standing; undergraduate methodologies are covered. Cross-listed with ECE 462/ECE 562. preparation in calculus and probability & statistics; and computer literacy. MSIM 563. Design and Modeling of Autonomous Robotic Systems. 3 MSIM 603. Simulation Design. 3 Credits. Credits. Course develops the computer software skills necessary for the design Course focuses on autonomous robotics systems with emphasis on using and development of simulation software. Topics covered include software modeling and simulation (M&S) for system level design and testing. architectures, software engineering, software design, object-oriented Fundamental concepts associated with autonomous robotic systems are programming, abstract data types and classes, data structures, algorithms, discussed. Course topics include: robotic control, architectures, and sensors and testing and debugging techniques. Software design and development as well as more advanced concepts such as error propagation, localization, of simulation systems (discrete-event, continuous, and Monte Carlo) mapping and autonomy. Design strategies that leverage M&S to accelerate are emphasized. Prerequisite: MSIM 602 and an introductory computer the development and testing of sophisticated autonomous robotic algorithms programming course. for individual or teams of robots are covered. Pre- or corequisite: CS 150. MSIM 607. Machine Learning I. 3 Credits. MSIM 570. Foundations of Cyber Security. 3 Credits. Course provides a practical treatment of design, analysis, implementation Course provides an overview of theory, tools and practice of cyber security and applications of algorithms. Topics include multiple learning models: and information assurance through prevention, detection and modeling linear models, neural networks, support vector machines, instance-based of cyber attacks and recovery from such attacks. Techniques for security learning, Bayesian learning, genetic algorithms, ensemble learning, modeling, attack modeling, risk analysis and cost-benefit analysis are reinforcement learning, unsupervised learning, etc. (Cross listed with described to manage the security of cyber systems. Fundamental principles ECE 607). of cyber security and their applications for protecting software and information assets of individual computers and large networked systems MSIM 660. System Architecture and Modeling. 3 Credits. are explored. Anatomy of some sample attacks designed to compromise Students will learn the essential aspects of the system architecture paradigm confidentiality, integrity and availability of cyber systems are discussed. through environment and analysis of multiple architecture framework Prerequisites: CS 150 or ENGN 150. and enterprise engineering, such as IDEFO, TOGAF, DODAF and OPM. Emphasis on system modeling and enterprise engineering. (Cross listed with MSIM 574. Transportation Data Analytics. 3 Credits. ENMA 660). This course presents the basic techniques for transportation data analytics. It will discuss statistical modeling, prominent algorithms, and visualization MSIM 667. Cooperative Education. 1-3 Credits. approaches to analyze both small- and large-scale data sets generated from Available for pass/fail grading only. Student participation for credit based transportation systems. Practices of using different data for various real- on academic relevance of the work experience, criteria, and evaluation world traffic/transportation applications and decision making will also be procedures as formally determined by the program and the Cooperative discussed. Prerequisites: Basic probability and statistics (e.g., STAT 330); Education/Career Development Services program prior to the semester in any programming language such as C, Python or Java is beneficial but not which the work experience is to take place. required.

5 Department of Computational Modeling and Simulation Engineering MSIM 668. Internship. 1-3 Credits. MSIM 722. Cluster Parallel Computing. 3 Credits. Academic requirements will be established by the department and will This course provides detailed numerical step-by-step procedures to exploit vary with the amount of credit desired. Allows students an opportunity to parallel and sparse computation under MPI (Message Passing Interface) gain short duration career-related experience. Prerequisites: Approval by computer environments. Large-scale engineering/science applications are department and Career Development Services. emphasized. Simultaneous linear equations are discussed. MSIM 669. Practicum. 1-3 Credits. MSIM 725. Principles of Combat Modeling and Simulation. 3 Credits. Academic requirements will be established by the graduate program Principles of combat modeling and simulation. Introduction including director and will vary with the amount of credit desired. Allows students history, basic definitions, and best practice. Algorithms for modeling an opportunity to gain short-duration career related experience. Student movement, sensing effects and behavior. Overview of modern combat is usually employed–this is an additional project beyond the duties of the models. Interoperability and integration into operational environments. student’s employment. Prerequisites: MSIM 603. MSIM 670. Cyber Systems Engineering. 3 Credits. MSIM 730. Simulation Formalisms. 3 Credits. This course provides an overview of functioning of cyber systems including The focus of the course is on identification and investigation of how a computer interacts with the outside world. The composition of critical mathematical and logical structures that form the foundation for infrastructure and functioning of different engineered systems that form computational simulation. Topics include: foundations of simulation theory critical infrastructure are discussed. Mutual dependence and interactions in logic, discrete mathematics, and computability; simulation formalisms, between cyber systems and other engineered systems and the resulting including DEVS; interoperability protocols; and computational complexity. security risks are also explored. (Cross-listed with ENMA 670.). MSIM 741. Principles of Visualization. 3 Credits. MSIM 673. Threat Modeling and Risk Analysis. 3 Credits. Well-designed graphical media capitalizes on human facilities for processing This course discusses how to develop cyber threat models using attack visual information and thereby improves comprehension, memory, graphs/trees, STRIDE, Universal Modeling Language (UML), attack graphs/ inference, and decision making. This course teaches techniques and trees and common of risk analysis tools. Course also discusses the need for algorithms for creating effective visualizations based on principles and quantitative security analysis and formal validation of security models and techniques from graphic design, visual art, perceptual psychology and basic principles of formal model validation. (Cross-listed with ENMA 673.). cognitive science. Both users and developers of visualization tools and MSIM 695. Topics in Modeling and Simulation. 3 Credits. systems will benefit from this course. Special topics of interest with emphasis placed on recent developments in MSIM 742. Synthetic Environments. 3 Credits. modeling and simulation. The course covers the theory and techniques for building effective and MSIM 697. Independent Study in Modeling and Simulation. 3 Credits. efficient synthetic environments for modeling and simulation applications. Individual study selected by the student. Supervised and approved by Topics include physics, artificial intelligence, virtual reality, and advanced a faculty member with the approval of the graduate program director. modeling and rendering. The emphasis is on producing visually realistic Prerequisites: permission of instructor or graduate program director. synthetic environments based on effective approximations of physics and other related principles. Prerequisites: MSIM 541 or equivalent. MSIM 699. Thesis. 1-6 Credits. Research leading to the Master of Science thesis. Prerequisites: permission MSIM 751. Advanced Analysis for Modeling and Simulation. 3 Credits. of instructor and graduate program director. An introduction to stochastic dependence and Bayesian analysis techniques for conducting modeling and simulation studies. Topics include: measures of MSIM 702. Systemic Decision Making. 3 Credits. dependence, common multivariate distributions, sampling from multivariate As machine age problems have given way to systems age messes, the distributions, elementary time series models and Bayesian statistics. underlying complexity associated with understanding these situations has Prerequisites: MSIM 451 or MSIM 551. increased exponentially. Accordingly, the methods we use to address these situations must evolve as well. This course will introduce students to a MSIM 762. Applied Medical Image Analysis. 3 Credits. method for thinking holistically about problems and messes conceptually Course explores hands-on exposure to state-of-the-art algorithms in medical founded in systems theory. This paradigm, known as systemic thinking, will image analysis, which builds on open-source software (Insight Segmentation be contrasted with traditional systematic thinking, and practical guidelines and Registration Toolkit - ITK), as well as the principles of medical image for the deployment of a systemic thinking approach will be provided. This acquisition in the modalities of clinical interest. Medical imaging modalities paradigm will increase the student's ability to make rational decisions in - X-rays, CT, and MRI/ITK image pipeline; image enhancement, feature complex environments. (Cross listed with ENMA 702/ENMA 802.). detection; segmentation - basic techniques, feature-based classification and clustering, graph cuts, active contour and surface models; surface MSIM 703. Optimization Methods. 3 Credits. and volume meshing; registration - transformations, similarity criteria; Covers advanced methods in and Optimization. Focus shape and appearance models are all explored and discussed in this course. will be on developing models and their applications in different domains Prerequisites: Knowledge of C++ and object-oriented programming. including manufacturing and service. Modern optimization tools will be used to implement models for case studies, projects and research papers. The MSIM 772. Modeling Global Events. 3 Credits. knowledge of programming and spreadsheets is expected. Contact instructor Modeling Global Events introduces modeling and simulation as a tool for more details. (Cross-listed with ENMA 703). for expanding our understanding of events that have shaped the global environment of the 21st century. Students will review real-world case studies MSIM 711. Finite Element Analysis. 3 Credits. and then analyze these case studies via system dynamics, agent-based, social The purpose of the course is to provide an understanding of the finite network, and game theory modeling paradigms. This course is designed to element method (FEM) as derived from an integral formulation perspective. develop empirical research skills, conceptual modeling expertise, and model The course will demonstrate the solutions of (1-D and 2-D) continuum construction. Students will understand how to analyze, verify, and validate a mechanics problems such as solid mechanics, fluid mechanics and heat model. transfer. Prerequisites: permission of the instructor. MSIM 774. Transportation Network Flow Models. 3 Credits. MSIM 715. High Performance Computing and Simulations. 3 Credits. This course provides a rigorous introduction to transportation network Introduction to modern high performance computing platforms including modeling, with special emphasis on network equilibrium problems. top supercomputers and accelerators. Discussion of parallel architectures, Topics include: elementary graph theory, shortest path problem nonlinear performance, programming models, and software development issues. Case optimization, optimization of univariate functions, deterministic and studies of scientific and engineering simulations will be explored. Students stochastic user equilibrium. (Cross-listed with CEE 774 and MSIM 774). will have an opportunity to work on parallelization of problems from their research areas. Project presentations are required.

Department of Computational Modeling and Simulation Engineering 6 MSIM 775. Transportation Network Algorithms. 3 Credits. MSIM 830. Simulation Formalisms. 3 Credits. Fundamental models and algorithms in optimization, stochastic modeling The focus of the course is on identification and investigation of and parallel computing will be discussed and illustrated with transportation mathematical and logical structures that form the foundation for applications. (Cross-listed with CEE 775 and CEE 875). computational simulation. Topics include: foundations of simulation theory MSIM 776. Simulation Modeling in Transportation Networks. 3 in logic, discrete mathematics, and computability; simulation formalisms, Credits. including DEVS; interoperability protocols; and computational complexity. Principles of simulation modeling, microscopic, mesoscopic, and MSIM 841. Principles of Visualization. 3 Credits. macroscopic traffic simulation models. Course explores diver behavior in Well-designed graphical media capitalizes on human facilities for processing networks, calibration and validation of traffic simulation models, and use of visual information and thereby improves comprehension, memory, traffic simulation software. inference, and decision making. This course teaches techniques and MSIM 780. Machine Learning II. 3 Credits. algorithms for creating effective visualizations based on principles and Advanced topics in machine learning and pattern recognition systems. Data techniques from graphic design, visual art, perceptual psychology and reduction techniques including principle component analysis, independent cognitive science. Both users and developers of visualization tools and component analysis and manifold learning. Introduction to sparse coding and systems will benefit from this course. deep learning for data representation and feature extraction. (Cross-listed MSIM 842. Synthetic Environments. 3 Credits. with ECE 780 and ECE 880). Prerequisite: MSIM 607 or equivalent. The course covers the theory and techniques for building effective and MSIM 795. Topics in Modeling and Simulation. 3 Credits. efficient synthetic environments for modeling and simulation applications. Special topics of interest with emphasis placed on recent developments in Topics include physics, artificial intelligence, virtual reality, and advanced modeling and simulation. modeling and rendering. The emphasis is on producing visually realistic synthetic environments based on effective approximations of physics and MSIM 797. Independent Study in Modeling and Simulation. 3 Credits. other related principles. Prerequisites: MSIM 541 or equivalent. Individual study selected by the student. Supervised and approved by a faculty member with the approval of the graduate program director. MSIM 851. Advanced Analysis for Modeling and Simulation. 3 Credits. Prerequisites: permission of instructor or graduate program director. An introduction to stochastic dependence and Bayesian analysis techniques for conducting modeling and simulation studies. Topics include: measures of MSIM 802. Systemic Decision Making. 3 Credits. dependence, common multivariate distributions, sampling from multivariate As machine age problems have given way to systems age messes, the distributions, elementary time series models and Bayesian statistics. underlying complexity associated with understanding these situations has Prerequisites: MSIM 451 or MSIM 551. increased exponentially. Accordingly, the methods we use to address these situations must evolve as well. This course will introduce students to a MSIM 862. Applied Medical Image Analysis. 3 Credits. method for thinking holistically about problems and messes conceptually Course explores hands-on exposure to state-of-the-art algorithms in medical founded in systems theory. This paradigm, known as systemic thinking, will image analysis, which builds on open-source software (Insight Segmentation be contrasted with traditional systematic thinking, and practical guidelines and Registration Toolkit - ITK), as well as the principles of medical image for the deployment of a systemic thinking approach will be provided. This acquisition in the modalities of clinical interest. Medical imaging modalities paradigm will increase the student's ability to make rational decisions in - X-rays, CT, and MRI/ITK image pipeline; image enhancement, feature complex environments. (Cross listed with ENMA 702/ENMA 802.). detection; segmentation - basic techniques, feature-based classification and clustering, graph cuts, active contour and surface models; surface and MSIM 803. Optimization Methods. 3 Credits. volume meshing; registration - transformations, similarity criteria; shape and Covers advanced methods in Operations Research and Optimization. Focus appearance models are all explored and discussed in this course. will be on developing models and their applications in different domains including manufacturing and service. Modern optimization tools will be MSIM 872. Modeling Global Events. 3 Credits. used to implement models for case studies, projects and research papers. The Modeling Global Events introduces modeling and simulation as a tool knowledge of programming and spreadsheets is expected. Contact instructor for expanding our understanding of events that have shaped the global for more details. (Cross-listed with ENMA 803). environment of the 21st century. Students will review real-world case studies and then analyze these case studies via system dynamics, agent-based, social MSIM 811. Finite Element Analysis. 3 Credits. network, and game theory modeling paradigms. This course is designed to The purpose of the course is to provide an understanding of the finite develop empirical research skills, conceptual modeling expertise, and model element method (FEM) as derived from an integral formulation perspective. construction. Students will understand how to analyze, verify, and validate a The course will demonstrate the solutions of (1-D and 2-D) continuum model. mechanics problems such as solid mechanics, fluid mechanics and heat transfer. Prerequisites: permission of the instructor. MSIM 874. Transportation Network Flow Models. 3 Credits. This course provides a rigorous introduction to transportation network MSIM 815. High Performance Computing and Simulations. 3 Credits. modeling, with special emphasis on network equilibrium problems. Introduction to modern high performance computing platforms including Topics include: elementary graph theory, shortest path problem nonlinear top supercomputers and accelerators. Discussion of parallel architectures, optimization, optimization of univariate functions, deterministic and performance, programming models, and software development issues. Case stochastic user equilibrium. (Cross-listed with CEE 774 and CEE 874). studies of scientific and engineering simulations will be explored. Students will have an opportunity to work on parallelization of problems from their MSIM 875. Transportation Network Algorithms. 3 Credits. research areas. Project presentations are required. Fundamental models and algorithms in optimization, stochastic modeling and parallel computing will be discussed and illustrated with transportation MSIM 822. Cluster Parallel Computing. 3 Credits. applications. (Cross-listed with CEE 775 and CEE 875). This course provides detailed numerical step-by-step procedures to exploit parallel and sparse computation under MPI (Message Passing Interface) MSIM 876. Simulation Modeling in Transportation Networks. 3 computer environments. Large-scale engineering/science applications are Credits. emphasized. Simultaneous linear equations are discussed. Principles of simulation modeling, microscopic, mesoscopic, and macroscopic traffic simulation models. Course explores driver behavior in MSIM 825. Principles of Combat Modeling and Simulation. 3 Credits. networks, calibration and validation of traffic simulation models, and use of Principles of combat modeling and simulation. Introduction including traffic simulation software. history, basic definitions, and best practice. Algorithms for modeling movement, sensing effects and behavior. Overview of modern combat models. Interoperability and integration into operational environments. Prerequisites: MSIM 603.

7 Department of Computational Modeling and Simulation Engineering MSIM 880. Machine Learning II. 3 Credits. Advanced topics in machine learning and pattern recognition systems. Data reduction techniques including principle component analysis, independent component analysis and manifold learning. Introduction to sparse coding and deep learning for data representation and feature extraction. (Cross-listed with ECE 780 and ECE 880). Prerequisite: MSIM 607 or equivalent. MSIM 892. Doctor of Engineering Project. 1-9 Credits. Directed individual study applying advanced level technical knowledge to identify, formulate and solve a complex, novel problem in Modeling and Simulation. MSIM 895. Topics in Modeling and Simulation. 3 Credits. Special topics of interest with emphasis placed on recent developments in modeling and simulation. MSIM 897. Independent Study in Modeling and Simulation. 1-3 Credits. Individual study selected by the student. Supervised and approved by a faculty member with the approval of the graduate program director. Prerequisites: permission of the instructor or graduate program director. MSIM 898. Research in Modeling and Simulation. 1-12 Credits. Supervised research prior to passing Ph.D. candidacy exam. Prerequisites: permission of the instructor and graduate program director. MSIM 899. Dissertation. 1-12 Credits. Directed research for the doctoral dissertation. Prerequisites: permission of the instructor and graduate program director. MSIM 998. Master's Graduate Credit. 1 Credit. This course is a pass/fail course for master's students in their final semester. It may be taken to fulfill the registration requirement necessary for graduation. All master's students are required to be registered for at least one graduate credit hour in the semester of their graduation. MSIM 999. Doctoral Graduate Credit. 1 Credit. This course is a pass/fail course doctoral students may take to maintain active status after successfully passing the candidacy examination. All doctoral students are required to be registered for at least one graduate credit hour every semester until their graduation.

Department of Computational Modeling and Simulation Engineering 8