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Mojtaba Khanzadeh, PhD, earned his doctorate in Industrial Engineering from Mississippi State University and also received his second MSc degree in Statistics from Mississippi State University.

Khanzadeh’s research focuses on the effective utilization of high-dimensional, image-based data streams to monitor and predict the performance of complex metal printing processes. From a methodological viewpoint, his expertise focuses on the development of new tensor-based, feature extraction methodology for big data (at the scale of terabytes) generated from complex engineering systems; and use the developed method for the purpose of prediction, diagnosis, and optimization. The methodologies that he has developed are not limited to Additive Manufacturing applications, rather they have direct applicability to many other types of application domains including, healthcare applications, cybersecurity, power generation systems, financial engineering, smart grids and other data-rich systems.