Design automation and additive manufacturing achieve high heat transfer with complex 3D structures.
Davis J. McGregor, Ph.D. is Senior Manufacturing Scientist at Fast Radius. He is developing manufacturing intelligence algorithms for traditional and additive manufacturing technologies, including cost estimation, virtual validation, and design for manufacturability. He leads the development of Fast Radius’ framework for continuous feedback and improvement of machine learning algorithms.
Davis is an expert in data science, machine learning, computer vision, and statistical analysis for traditional and advanced manufacturing, including additive manufacturing. He has extensive experience analyzing manufacturing vision data from photographs, X-ray computed tomography, and variable focus microscopy. Davis holds a Ph.D. in Mechanical Engineering from the University of Illinois Urbana-Champaign. His dissertation was “Metrology Automation and Geometric Analysis for Additive Manufacturing.” His research focused on the development of optical metrology systems for high throughput analysis of parts with complex geometries. He also developed machine learning frameworks for predicting the quality of additively manufactured parts fabricated in a production environment.
Davis has authored 10 peer reviewed journal publications with over 160 citations. He has led educational workshops and presented at professional conferences on leveraging machine learning and software automation in the manufacturing field.
AM part accuracy and sources of variability in a factory.
2021 UIUC Image of Research semi-finalist.
How different countries responded, and exercise habits adapted, to COVID-19.