Program Overview
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:
Program Requirements
Common Core
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
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
Research/Methods Course(s)
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
Restricted Electives
Students must choose two courses: Course 1: 3 credits or more:
AET 648:
Advanced High Performance Engineering (1-3 credits)
- Examines advanced topics in high-performance engineering
ECON 562:
Econometrics (3 credits)
- Explores econometric modeling for forecasting and measurement
ECON 563:
Applied Econometrics of Financial Markets (3 credits)
- Covers quantitative methods for analyzing financial markets
EE 600:
Design Methods (3 credits)
- Utilizes EE computer modeling and simulation tools for design applications
EE 601:
Linear Systems Analysis (3 credits)
- Analyses continuous and discrete multivariate systems, stochastic and non-stochastic systems, and sampled data systems
EE 603:
Non-Linear System Analysis (3 credits)
- Examines non-linear continuous and discrete systems and devices
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
GEOG 539:
Transportation Modeling & GIS (4 credits)
- Develops an understanding of spatial organization, network analysis, allocation methods, and urban transportation
GEOG 571:
Digital Field Mapping with GPS (4 credits)
- Teaches practical field survey techniques using GPS and other tools
GEOG 573:
Intermediate GIS (4 credits)
- Enhances students' GIS knowledge for geospatial data manipulation and analysis
GEOG 574:
Introduction to Remote Sensing (4 credits)
- Provides an overview of remote sensing theories and techniques for image processing and analysis
GEOG 575:
Applied Remote Sensing & GIS (4 credits)
- Develops advanced remote sensing capabilities, including image processing and independent research skills
GEOG 576:
Spatial Statistics (3 credits)
- Covers descriptive statistics, probability, hypothesis testing, spatial analysis, and spatial data representation Course 2: 2 credits or more:
GEOG 577:
Topics in Techniques (1-3 credits)
- Offers specialized coursework in various geographic techniques, such as manual cartography or GPS use
GEOG 578:
Spatial Analysis with GIS (3 credits)
- Examines frameworks for spatial analysis and quantitative methods for studying spatial patterns
GEOG 579:
GIS Practicum (1-4 credits)
- Provides supervised project work in GIS using real-world problems and industry connections
GEOG 580:
Seminar (1-4 credits)
- Explores varying topics in geography, from environmental conservation to geographic techniques
HLTH 575:
Biostatistics (3 credits)
- Introduces statistical analysis in the health sciences, examining concepts and methods for solving health-related problems
IT 544:
Data Analytics (4 credits)
- Examines big data concepts, including strategies, techniques, and evaluation methods
IT 582:
Human Computer Interaction (4 credits)
- Investigates principles of user interface design, including perception, cognition, and evaluation techniques
MATH 522:
Partial Differential Equations (4 credits)
- Focuses on the theory, computations, and applications of partial differential equations and Fourier series
MATH 525:
Mathematical Modeling (4 credits)
- Studies modeling strategies for continuous and discrete problems and real-world applications in sciences and technology
MATH 570:
Numerical Analysis I (4 credits)
- Introduces numerical methods for solving mathematical problems using technology, covering errors, solutions to equations, and interpolation
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
MATH 590:
Workshop (1-4 credits)
- Provides focused learning on select mathematical topics
MATH 620:
Applied Mathematics (3 credits)
- Utilizes applied mathematics to solve scientific problems within natural sciences, engineering, and economics
MATH 621:
Topics in Applied Mathematics (3 credits)
- Explores distinct aspects of applied mathematics and may be repeated for different topics
MATH 628:
Numerical Optimization (3 credits)
- Covers techniques for solving continuous optimization problems, including large-scale optimization methods
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
MATH 674:
Computations in Linear Algebra (3 credits)
- Investigates advanced linear algebra topics such as eigenvalue problems, least-square problems, and iterative methods
MATH 680:
Topics in Mathematics (1-4 credits)
- Explores graduate-level mathematics, with each topic potentially differing
MATH 695:
Workshop (1-4 credits)
- Focused study of a specific mathematical topic
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
ME 601:
Advanced Computational Methods in Engineering (3 credits)
- Investigates advanced computational methods for solving linear systems, non-linear equations, and more
ME 602:
Advanced CAE (3 credits)
- Explores cutting-edge computer-aided engineering tools and techniques
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
