Monitoring and Modeling of Additive Manufacturing Processes.
Understanding and monitoring the root cause of defect formation in Laser Powder Bed Fusion (LPBF), Directed Energy Deposition (DED), Aerosol Jet Printing (AJP), Fused Freeform Fabrication (FFF), and Binder Jetting (BJ).
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Monitoring and Modeling of Ultraprecision Processes.
Understanding and monitoring the process dynamics of Ultraprecision machining (UPM), semiconductor chemical mechanical planarization (CMP), lapping, and magneto-rheological free-form finishing (MR3F)
Big Data Analytics and Artificial Intelligence.
Sensor fusion, Neural networks, and Bayesian learning in Advanced Manufacturing
Decision theory and spectral graph theoretic sensor fusion for in-process quality assurance in additive manufacturing. Recurrent neural networks for surface finish monitoring in ultraprecision machining. Bayesian decision theoretic models for process monitoring of defects in semiconductor polishing
Deep learning and statistical models in healthcare
Detection of epileptic seizures, cardiac anomalies, and neuropsychological degradation using machine learning models.
Projects and Funding
National Science Foundation – CMMI, Service, Manufacturing and Operations Research Program, Grant Number: CMMI 1719388, Biosensor Data Fusion for Real-time Monitoring of Global Neurophysiological Function. Project Duration: September 2015 - 2018.
National Science Foundation – CMMI, Cyber Physical Systems Program, Grant Number: CMMI 1739696, CPS: Medium: Collaborative Research: Cyber-Enabled Online Quality Assurance for Scalable Additive Bio-Manufacturing. Project Duration: September 2017 - 2021.