In his CAREER project, Moghaddass will address the efficient operation and health monitoring of complex, sensor-driven engineered systems and promote both the progress of science and advance economic competitiveness and national prosperity. The project focuses on developing a new generation of flexible and large-scale mathematical and computational models for real-time system health monitoring inspired by dynamic structures and networks. The results of this multidisciplinary CAREER project are applicable in a number of engineering systems, including but not limited to, wind turbines, power systems and other sensor-intensive engineering systems. The project also aims to enhance the participation of underrepresented minorities in the Science, Technology, Engineering and Math (STEM) fields, particularly in data analytics, data-driven decision making and computing science careers.
“Dr. Moghaddass’ research will provide a new framework for real-time decision-making that applies data science to renewable power sources and energy-intensive industries,” said Jean-Pierre Bardet, dean of UMCoE. “He is an emerging leader in his field and I am pleased that NSF has recognized him through this prominent award.”
“My long-term CAREER goal is to contribute to the development of the next generation of trustable and scalable data-driven methods utilizing real-time heterogeneous data collected from various Internet of Things (IOT) sensors and connected devices that enable more timely, accurate, and targeted decision making and control,” explained Moghaddass. “I am very honored and excited to receive the NSF Career award. This grant will allow me to make a significant impact on data analytics using large-scale sensor data.”
NSF CAREER Awards are prestigious and competitive awards given to junior faculty who exemplify the role of teacher-scholar through outstanding research, excellent education, and the integration of education and research within the context of the mission of their respective organizations.
Read more about Moghaddass’ research entitled, “A New Generation of Sensor-Driven Frameworks for Real-time Monitoring, Control, and Decision Making in Dynamic Systems.”
