John P. Mullen, Ph.D.
New Mexico State University
|Research:||Mobile Ad Hoc Networks - Automatically configuring mobile networks which operate with no permanent infrastructure and adapt to changing topology and conditions as needed.|
|Modeling AD Hoc Network Performance in OPNET - Using the OPNET simulation package to predict the impact of design choices on Mobile Ad Hoc Networks.|
- A collection of attempts to improve the quality of my instruction .
Application Files - Little ditties that I make available to students in my courses.
|IE 515 - Stochastic Process Modeling - An introduction to the use of stochastic processes in the modeling of physical and natural systems. Use of generating functions, conditional probability and expectation, Poisson processes, random walk models, Markov chains, branching processes, Markov processes, and queuing processes in an applied setting. Requires an elementary knowledge of calculus-based probability and statistics, as well as knowledge of differential equations.|
|IE 522 - Queueing Theory - Methods and modeling. Requires elementary knowledge of calculus-based probability and statistics.|
|IE 525 - Deterministic Network Analysis - Algorithms and modeling of problems involving cost minimization, capacity estimation, and least cost flow management. A background in elementary linear programming is helpful, but not necessary.|
|IE 531 - Survey of Operations Research Techniques - An introduction and overview of operations research methodology. This course introduces key methods to model and find solutions to a variety of optimization problems. Scope includes stochastic, as well as deterministic, techniques. Techniques include basic theory and the use of computer tools.|
|IE 534 - Nonlinear Programming - Theoretical and computational methods to solve optimization problems that have nonlinear elements. Unconstrained optimization, including Lagrange multipliers and Kuhn-Tucker theory. Constrained optimization, including several algorithms with a range of differing assumptions and advantages. Requires a background in differential calculus.|
|IE 545 - Characterizing Time-Dependent Data - Theory and techniques employed in the characterization of stochastic processes commonly found in engineering applications. Requires elementary knowledge of calculus-based probability and statistics.|
|IE 561 - Advanced Industrial Safety - Regulation as well as qualitative, and quantitative methods to achieve and maintain safety in the workplace. Prerequisite: graduate status in engineering.|
|IE 569 - Stochastic Simulation Concepts and Techniques- While other courses on simulation subject focus on modeling, this course focuses on specific features of such simulation that are important when one wishes to realistically predict behavior in an uncertain world. Two key topics are how to avoid the pitfalls due to pseudo random number generators and the nature and impact of auto correlation. Other topics include methods to validate models, improve simulation efficiency, and improve simulation effectiveness.|
|IE 610 - Network Algorithmic Design - Selected advanced topics in operations research. Restricted to IE Ph.D. students who have passed their qualifying exam. Specific topics differ from offering to offering. May be repeated for up to 6 credits.|
|IE 620 - Topics in Computer Modeling - Selected advanced topics in computer modeling, simulation, and output analysis. Restricted to IE Ph.D. students who have passed their qualifying exam. Specific topics differ from offering to offering. May be repeated for up to 6 credits.|
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