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Data processing and visualization is increasingly important in today’s data driven world, where proper management of data can facilitate the integration and evaluation of systems and projects. The goal of this class is to provide engineers with practical and applicable data science skills, including data aggregation and filtering, intuitive data exploration, effective communication of patterns, summaries, and findings, and methods of archiving for data sharing or future use. This class combines principles and theories of information visualization and data management with implementation techniques centered around the R statistical software program. Previous experience with R is not required, but a basic working knowledge of, or willingness to learn, will help students in this class.
Credit not allowed for both ENGR 580a5 and SYSE 541.
ECE 303 or STAT 303 or STAT 315.
Dr. Erika Gallegos’ research is centered on integrating humans with complex systems to enhance safety and performance in the design and evaluation of new and existing infrastructure.
Dr. Gallegos’ work focuses on modeling human behavior and cognitive workload over time to evaluate the interactions between humans and machines, with an emphasis on developing appropriate trust and maintaining situational awareness of human operators with autonomous systems. Her research is primarily applied to the transportation domain; with a current focus of integrating smart technology (e.g., connected vehicles, connected infrastructure, autonomous vehicles) into the transportation system while facilitating safety for all users (e.g., automated, non-automated, motorized, non-motorized).
Her education and research backgrounds are in civil engineering, industrial and systems engineering, transportation engineering, and human factors.
Learn more at: http://www.engr.colostate.edu/se/erika-miller/