This course provides an introduction to network and combinatorial optimization at the level of a second graduate course in optimization. Designed to complement SYS 6003, but the course is not …
Presents the foundations of mathematical modeling and optimization, with emphasis on problem formulation and solution techniques. Includes applications of linear programs, nonlinear programs, and combinatorial models, as well as a …
This course is an introduction to the theory of the industrial organization (from a game-theoretic perspective) and its applications to industries with strong engineering content (electricity, telecommunications, software and hardware, …
The goal of this course is to develop an operational understanding of the basic tools of probabilistic modeling, including (i) a review of undergraduate probability, (ii) introduction to Bernoulli and …
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 …
This course will teach students the required skills, concepts, and algorithms to develop mobile robots that act autonomously in complex environments. The main emphasis is on mobile robot locomotion and …
This topic covers principles of human factors engineering, understanding and designing systems that take into account human capabilities and limitations from cognitive, physical, and social perspectives. Models of human performance …
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 …
Special Topics in Distance Learning
Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.
Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.
Cyber-physical systems (CPS) are smart systems that include co-engineered interacting networks of physical and computational components. This course will teach students the required skills to analyze the CPS that are …
This course is designed to develop cross-competency in the technical, analytical, and professional capabilities necessary for the emerging field of Cyber-Physical Systems (CPS). It provides convergence learning activities based around …
Detailed study of graduate course material on an independent basis under the guidance of a faculty member.
Formal record of student commitment to project research under the guidance of a faculty advisor. Registration may be repeated as necessary.
Under faculty guidance, students apply the principles of systems methodology, design, and management along with the techniques of systems and decision sciences to systems analysis and design cases. The primary …
Provides a non-measure theoretic treatment of advanced topics in the theory of stochastic processes, focusing particularly on denumerable Markov processes in continuous time and renewal processes. The principal objective is …
An introduction to time series analysis and forecasting. Topics include exploratory data analysis for time-correlated data, time series modeling, spectral analysis, filtering, and state-space models. Time series analysis in both …
Bayesian theory of forecasting and decision making; judgmental procedures and statistical models for probabilistic forecasting, post-processors of deterministic forecasts; sufficient comparisons of forecasters, verification of forecasts, combining forecasts; optimal decision …