Modeling and Simulation GC

Program Overview

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This Master's program in Modeling and Simulation provides a comprehensive foundation in core concepts and methodologies, with a focus on data-driven modeling and big data analysis. Students can tailor their studies by choosing from a wide range of restricted electives in fields such as engineering, economics, geography, and mathematics. The program prepares graduates for careers in industries that rely on modeling and simulation for decision-making and problem-solving.

Program Outline

Outline:

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Program Requirements

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Common Core

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MDSM 601:

Introduction to Modeling and Simulation (4 credits)

• Focuses on core modeling and simulation concepts and methodologies
• Includes extensive computer lab exercises and a student-designed project

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MDSM 691:

Seminar in Modeling and Simulation (1 credit)

• Students present and defend their modeling and simulation work, typically completed in a required capstone/individual study course

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Research/Methods Course(s)

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MDSM 602:

Data-Driven Modeling & Big Data Analysis (4 credits)

• Covers advanced concepts, techniques, and applications in data-driven modeling and big data analysis
• Involves computer lab exercises, case studies, and a student-designed term project

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Restricted Electives

Students must choose two courses: Course 1: 3 credits or more:

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AET 648:

Advanced High Performance Engineering (1-3 credits)

• Examines advanced topics in high-performance engineering

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ECON 562:

Econometrics (3 credits)

• Explores econometric modeling for forecasting and measurement

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ECON 563:

Applied Econometrics of Financial Markets (3 credits)

• Covers quantitative methods for analyzing financial markets

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EE 600:

Design Methods (3 credits)

• Utilizes EE computer modeling and simulation tools for design applications

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EE 601:

Linear Systems Analysis (3 credits)

• Analyses continuous and discrete multivariate systems, stochastic and non-stochastic systems, and sampled data systems

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EE 603:

Non-Linear System Analysis (3 credits)

• Examines non-linear continuous and discrete systems and devices

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EE 651:

Biomedical Engineering I (3 credits)

• Applies mathematical modeling to living systems, covering principles of metabolic processes, cardiovascular and nervous systems, and disease states

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GEOG 539:

Transportation Modeling & GIS (4 credits)

• Develops an understanding of spatial organization, network analysis, allocation methods, and urban transportation

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GEOG 571:

Digital Field Mapping with GPS (4 credits)

• Teaches practical field survey techniques using GPS and other tools

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GEOG 573:

Intermediate GIS (4 credits)

• Enhances students' GIS knowledge for geospatial data manipulation and analysis

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GEOG 574:

Introduction to Remote Sensing (4 credits)

• Provides an overview of remote sensing theories and techniques for image processing and analysis

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GEOG 575:

Applied Remote Sensing & GIS (4 credits)

• Develops advanced remote sensing capabilities, including image processing and independent research skills

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GEOG 576:

Spatial Statistics (3 credits)

• Covers descriptive statistics, probability, hypothesis testing, spatial analysis, and spatial data representation
Course 2: 2 credits or more:

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GEOG 577:

Topics in Techniques (1-3 credits)

• Offers specialized coursework in various geographic techniques, such as manual cartography or GPS use

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GEOG 578:

Spatial Analysis with GIS (3 credits)

• Examines frameworks for spatial analysis and quantitative methods for studying spatial patterns

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GEOG 579:

GIS Practicum (1-4 credits)

• Provides supervised project work in GIS using real-world problems and industry connections

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GEOG 580:

Seminar (1-4 credits)

• Explores varying topics in geography, from environmental conservation to geographic techniques

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HLTH 575:

Biostatistics (3 credits)

• Introduces statistical analysis in the health sciences, examining concepts and methods for solving health-related problems

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IT 544:

Data Analytics (4 credits)

• Examines big data concepts, including strategies, techniques, and evaluation methods

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IT 582:

Human Computer Interaction (4 credits)

• Investigates principles of user interface design, including perception, cognition, and evaluation techniques

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MATH 522:

Partial Differential Equations (4 credits)

• Focuses on the theory, computations, and applications of partial differential equations and Fourier series

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MATH 525:

Mathematical Modeling (4 credits)

• Studies modeling strategies for continuous and discrete problems and real-world applications in sciences and technology

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MATH 570:

Numerical Analysis I (4 credits)

• Introduces numerical methods for solving mathematical problems using technology, covering errors, solutions to equations, and interpolation

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MATH 571:

Numerical Analysis II (4 credits)

• Extends concepts from MATH 570, tackling topics such as the algebraic eigenvalue problem, least-squares approximation, and differential equations

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MATH 590:

Workshop (1-4 credits)

• Provides focused learning on select mathematical topics

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MATH 620:

Applied Mathematics (3 credits)

• Utilizes applied mathematics to solve scientific problems within natural sciences, engineering, and economics

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MATH 621:

Topics in Applied Mathematics (3 credits)

• Explores distinct aspects of applied mathematics and may be repeated for different topics

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MATH 628:

Numerical Optimization (3 credits)

• Covers techniques for solving continuous optimization problems, including large-scale optimization methods

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MATH 672:

Numerical Analysis of Differential Equations (3 credits)

• Advanced coursework in solving ordinary and partial differential equations numerically, encompassing error control and step size techniques

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MATH 674:

Computations in Linear Algebra (3 credits)

• Investigates advanced linear algebra topics such as eigenvalue problems, least-square problems, and iterative methods

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MATH 680:

Topics in Mathematics (1-4 credits)

• Explores graduate-level mathematics, with each topic potentially differing

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MATH 695:

Workshop (1-4 credits)

• Focused study of a specific mathematical topic

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ME 550:

Finite Element Method (3 credits)

• Introduces energy and residual approaches of the finite element method, solving stress analysis and fluid and heat transfer problems

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ME 601:

Advanced Computational Methods in Engineering (3 credits)

• Investigates advanced computational methods for solving linear systems, non-linear equations, and more

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ME 602:

Advanced CAE (3 credits)

• Explores cutting-edge computer-aided engineering tools and techniques

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ME 603:

Computational Fluid Mechanics and Heat Transfer (3 credits)

• Utilizes numerical methods to solve partial differential equations commonly encountered in fluid mechanics and heat transfer fields