This course is an introduction to the theory, methods, and applications of risk analysis and systems engineering. The topics include research and development priorities, risk-cost-benefit analysis, emergency management, human health and safety, environmental risk, extreme events, infrastructure resilience, system interdependencies, and enterprise systems. Corequisites: a course in probability (APMA 3100 or APMA 3110 or Math 3100).

Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.

A design project extending throughout the fall and spring semesters. Involves the study of a real-world, open-ended situation, including problem formulation, data collection, analysis and interpretation, model building and analysis, and generation of solutions. Students work on the same project with the same team in SYS 4053 and 4054 in subsequent semesters.  Pre-requisites: SYS 2001 and SYS 2202 and FOUR of the following (SYS 3021 or SYS 3023 or SYS 3034 or SYS 3060 or  SYS 3062)

Independent study or project research under the guidance of a faculty member. Offered as required. Prerequisite: As specified for each offering.

Provides an introduction to the problems encountered when integrating large systems, and also presents a selection of specific technologies and methodologies used to address these problems. Includes actual case-studies to demonstrate systems integration problems and solutions. A term project is used to provide students with the opportunity to apply techniques for dealing with systems integration. Prerequisite: SYS 6001 or instructor permission.

An introduction to the analysis, design and evaluation of human-centered systems. User interaction can be designed to leverage the strengths of people in controlling automation and analyzing data. Topics include Task, User and Work Domain Analysis, User Interface Design Principles, Human Cognition and Information Processing, Human Perception, and Usability Testing. Graduate version includes separate project review sessions.

A first graduate course covering the theory and practice of discrete-event stochastic simulation. Coverage includes Monte Carlo methods and spreadsheet applications, generating random numbers and variates, specifying input probability distributions, discrete-event simulation logic and computational issues, review of basic queueing theory, analysis of correlated output sequences, model verification and validation, experiment design and comparison of simulated systems, and simulation optimization. Emphasis includes state-of-the-art simulation programming languages with animation on personal computers. Applications address operations in manufacturing, distribution, transportation, communication, computer, health care, and service systems. Prerequisite: SYS 6005 or equivalent background in probability, statistics, and stochastic processes.

The goals of this course are to educate graduate students in SEAS in the ethical conduct of research & publication, and to facilitate the thoughtful integration of ethics into their engineering research & practice. This is done by i) engaging students in deliberative readings, discussion, & writing about EERP, and ii) using cases to consider the ethical dimensions of engineering and resources to support the engineer facing ethical dilemmas.

A study of technological systems, where decisions are made under conditions of risk and uncertainty. Topics include conceptualization (the nature, perception, and epistemology of risk, and the process of risk assessment and management) systems engineering tools for risk analysis (basic concepts in probability and decision analysis, event trees, decision trees, and multiobjective analysis), and methodologies for risk analysis. Prerequisite: APMA 3100, SYS 3021, or equivalent.

For master's students.