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 analysis for trade-studies; presentation of system evaluation and analysis results. Illustrates the concepts and processes of systems evaluations using case studies. Pre-reqs: APMA 3120, SYS 2001, & SYS 3021.

A third-year level undergraduate course focused on a topic not normally covered in the course offerings. The topic usually reflects new developments in the systems and information engineering field. Offering is based on student and faculty interests.Prerequisites: Instructor Permission

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 time Markov chains, the Poisson Process, Non-Stationary Poisson Processes, Markov Decision Processes, Queueing Theory, and other selected topics. Prerequisite: APMA 3100 or MATH 3100.

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 variety of applications. Building on multiple regression, the course also covers principal component analysis, analysis of variance and covariance, logistic regression, time series methods, and clustering. Prerequisite: CS 2100, APMA 3100 and APMA 3120.

Introduction to deterministic optimization models: theory, algorithms, and applications. Coverage begins with highly structured network optimization models and ends with unstructured linear optimization models. Applications include (1) telecommunications network planning and design, (2) design and utilization of transportation and distribution networks, and (3) project management and scheduling. Corequisite: SYS 2001 and APMA 3080.

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-requisite:  SYS 4053

A first course in the theory & practice of discrete-event simulation. Monte Carlo methods, generating random numbers & variates, spreadsheet add-ins & applications, sampling distributions & confidence intervals, input analysis & distribution fitting. Discrete-event dynamic systems, modeling, simulation logic & data structures, output analysis, model verification & validation, comparing alternative systems, simulation optimization, case studies. Prerequisite: CS 2100, APMA 3100, and APMA 3120

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.

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 kinematics, control, sensing, localization, mapping, path planning, and motion planning. Besides theory, students are exposed to simulation environments and lab exercises with real robotic systems.

An introduction to the fundamentals for the analysis, design and evaluation of human-centered systems. For example, user interaction can be designed to leverage the strengths of people in controlling automation and analyzing data. Course topics include Task, User and Work Domain Analysis, User Interface Design Principles, Human Cognition and Information Processing (Top-Down Design), Human Perception (Bottom-Up Design), and Usability Testing. Corequisite: SYS 2001.