Journal of Computing and Information Science in Engineering

Rai, Ph.D.
Rahul Rai

Areas of Interest

Clemson University, USA
Dr. Rahul Rai joined the Department of Automotive Engineering in 2020 as Dean’s Distinguished Professor in the Clemson University International Center for Automotive Research (CU-ICAR). He directs the Geometric Reasoning and Artificial Intelligence Lab (GRAIL, which is located at both CU-ICAR and Center for Manufacturing Innovation (CMI). Previously, he served on the Mechanical and Aerospace Engineering faculty at the University at Buffalo-SUNY (2012-2020). Dr. Rai also has industrial research center experiences at United Technology Research Center (UTRC) and Palo Alto Research Center (PARC). Dr. Rai has authored or co-authored articles in journals, conference proceedings, technical reports and book chapters. Dr. Rai is currently an Associate Editor for the ASME Journal of Computing and Information Science in Engineering (JCISE). Within ASME Computers and Information in Engineering (CIE) division, Dr. Rai serves as a Reviewer for ASME Journal of Mechanical Design, Research in Engineering Design, Journal of Engineering Design, Journal of Computer Aided Design (CAD), International Journal of Production Research (IJPR), International Journal of Intelligent Systems, Technology and Applications (IJISTA), Engineering Optimization, ASME- International Design Engineering Technical Conference-Design Automation Conference (DAC), Design Theory and Methodology Conference (DTM), Design for Manufacturing and Life Cycle Conferences (DFMLC). Dr. Rai is also the Local Chair for ASME-Design Engineering Technical Conference 2014, Secretary for ASME- Design Engineering Technical Conference – CIE Conference, and Session Chair in ASME-Design Engineering Technical Conference-Design Automation Conference (DAC). Dr. Rai received his PhD in Mechanical Engineering from the University of Texas at Austin, TX.

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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.


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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