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Research Overview Dr. Yang and his research team at USF aim to create a rigorous knowledge body for sensorbased complex systems monitoring, modeling and analysis. The research will ultimately contribute to a new paradigm where a complex system is autonomized and optimized at all scales. As shown in Figure 1 , industry in the 21 st century is investing in a variety of sensor networks and dedicated data centers to increase information visibility in both engineering and healthcare domains.
... e sensing brings the proliferation of big data (i.e., dynamic, nonlinear, nonstationary, high dimensional) that contains a wealth of information on the condition and status of a product, process or a system. Big Data presents a 'gold mine' of this era (21 st century). Innovations in industrial and systems engineering in this century will be highly dominated by "new methods and tools" to mine the big data and harness its power for new product development, problem solving and system optimization. Fig. 1. Research Roadmap of Complex Systems Monitoring, Modeling and Analysis Lab Nonlinear Dynamics and Chaos Engineering and physiological systems (e.g., nanoscale machining and human heart) involve greater levels of complexity and technical challenge. Much of the complexity emerges from nonlinear dynamics of the underlying process. In order to cope with system complexity and dynamic environments, modern industries are investing in a variety of sensors and data acquisition systems. However, most of existing approaches adopt linear methods and tools for sensor information processing. Traditional linear approaches interpret the regular structure, e.g., Complex Engineering and Biological Systems Theoretical Foundations Sensor-based system informatics and process control Big data analytics for knowledge discovery and decision making Signal-level fusion for quality and reliability improvement Sensor-based system prognosis, maintenance and optimization Monitoring: wireless sensor networks, supervisory control and data acquisition (SCADA)