Major dimensions of systems engineering will be covered and demonstrated through case studies: (1) The history, philosophy, art, and science upon which systems engineering is grounded; including system thinking and …
This course provides students with the background necessary to model, store, manipulate, and exchange information to support decision making. It covers Unified Modeling Language (UML), SQL, and XML; the development …
This course examines the lifecycle of engineered systems (ES) and the public policies developed to regulate them. It covers risks, costs, benefits, and equity as common evaluation criteria for ES …
Focuses on the evaluation of candidate system designs and design performance measures. Includes identification of system goals; requirements and performance measures; design of experiments for performance evaluation; techniques of decision …
This is an introductory course on modeling probabilistic systems. The emphasis will be on model formulation and probabilistic analysis. Topics to be covered include general stochastic processes, discrete and continuous …
This course shows how to use linear statistical models for analysis in engineering and science. The course emphasizes the use of regression models for description, prediction, and control in a …
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 …
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, …
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Detailed study of a selected topic determined by the current interest of faculty and students. Offered as required. Prerequisite: As specified for each offering.
Detailed study of a selected topic determined by the current interest of faculty and students. Prerequisite: As specified for each offering.
Independent study or project research under the guidance of a faculty member. Offered as required. Prerequisite: As specified for each offering.
Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.
Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular …
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 …
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, …
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 …
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 …
For master's students.
Interactions between robots and humans are influenced by form, function and expectations. Quantitative techniques evaluate performance of specific tasks and functions. Qualitative techniques are used to evaluate the interaction and …