Industrial engineering, operations research, and systems engineering are fields of study intended for individuals who are interested in analyzing and formulating abstract models of complex systems with the intention of improving system performance. Unlike traditional disciplines in engineering and the mathematical sciences, the fields address the role of the human decision-maker as key contributor to the inherent complexity of systems and primary benefactor of the analyses.
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At ISyE, we are a national leader in 10 core fields of specialization: Advanced Manufacturing, Analytics and Machine Learning, Applied Probability and Simulation, Data Science and Statistics, Economic Decision Analysis, Energy and Sustainable Systems, Health and Humanitarian Systems, Optimization, Supply Chain Engineering, and Systems Informatics and Control.
ISyE's faculty and staff members strive to provide a world-class educational experience for the Stewart School's undergraduate and graduate students, and to forge long-lasting relationships with ISyE alumni and industry partners. If you have benefited from a connection with an ISyE faculty or staff member, feel free to take a moment to send a thank-you note to that person via this web form.
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Description: Topics include conditional probability, density and distribution functions from engineering, expectation, conditional expectation, laws of large numbers, central limit theorem, and introduction to Poisson Processes.
Description: Discrete event simulation methodology emphasizing the statistical basis for simulation modeling and analysis. Overview of computer languages and simulation design applied to various industrial situations.
ISYE 3232 - Stochastic Manufacturing & Service Systems
Description: Methods for describing stochastic movements of material in manufacturing facilities, supply chain, and equipment maintenance networks. Includes analysis of congestion, delays, and inventory ordering policies.
Description: Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression, and analysis of variance. Crosslisted with MATH 3770 and CEE 3770.
Description: Advanced modeling and statistical concepts in discrete-event simulations; Monte Carlo simulation; estimation of error and risk; advanced input modeling techniques; comparison and optimization of systems.
Description: core concepts and techniques for economic decision analysis of complex capital investment problems that involve dimensions of time, uncertainty and strategy. Students are also introduced to basic terminology, concepts and issues relevant to financial engineering, financial management and corporate finance.
ISYE 4740 - Biologically Inspired Design (Cross Listed with BIOL/ME/MSE/PTFE)
Description: We examine evolutionary adaptation as a source for engineering design inspiration, utilizing principles of scaling, adaptability, and robust multi-functionality that characterize biological systems.