ASME

Journal of Computing and Information Science in Engineering

Jonathan Roy 
Corney, Ph.D.
Jonathan_Corney

Areas of Interest

CAD ANALYTICS
CROWDSOURCING
GEOMETRIC REASONING
University of Edinburgh, UK
Jonathan Corney has been investigating innovative, industrial applications of computing technology since the 1980s. He graduated in Mechanical Engineering in 1983 and then worked as a ‘junior robot designer’ for the Westinghouse Electric Corp. He subsequently became a researcher at Edinburgh University’s Department of Artificial Intelligence, before joining Heriot-Watt University as a lecturer, where he researched topics in mechanical CAD/CAM (e.g. feature recognition, 3D content based retrieval). He took up the chair of “Design and Manufacture” at the University of Strathclyde in 2007 where he investigated manufacturing applications of crowdsourcing; cloud interfaces for manufacturing, the interactive search of digital media and, most recently, the creation of ‘predictive CAD systems’ by leveraging data analytics. Currently he is Professor of Digital Manufacturing at the University of Edinburgh School of Engineering. He has published two books and over 80 papers on various aspects of CAD/CAM and advanced manufacturing. Software and algorithms resulting from his research have been incorporated in the commercial products of three different companies. His interests in CAD/CAM are complemented by research into various metal forming processes (e.g. Near Net Shape and novel Cold Forming Technologies) and his work as Co-Director of the ‘Scottish Institute of Remanufacturing’.

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Announcements

Special Issue on Geometric Data Processing and Analysis for Advanced Manufacturing

Geometric information, such as three-dimensional (3D) shapes and network topologies, has been increasingly explored in manufacturing research. For example, characterizing geometric information in 3D-printed parts, in-situ or ex-situ, opens opportunities for defect detection, quality improvement, and product customization. However, geometric data mining remains critically challenging. Geometric information is embedded in complex data structures, such as 3D point clouds, graphs, meshes, voxels, high-dimensional images, and tensors, which possess challenges for analysis due to their high-dimensionality, high-volume, unstructured, multimodality characteristics. Additional challenges stem from compromised data quality (e.g., noisy and incomplete data), the need for registration, etc.

Announcements

2023 Reviewer’s Recognition

The Editor and Editorial Board of the Journal of Computing and Information Science in Engineering would like to thank all of the reviewers for volunteering their expertise and time reviewing manuscripts in 2023. Serving as reviewers for the journal is a critical service necessary to maintain the quality of our publication and to provide the authors with a valuable peer review of their work.

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