ASME

Journal of Computing and Information Science in Engineering

Ram D.  
Sriram, Ph.D.
Ram Sriram 2021b

Areas of Interest

COMPUTER-AIDED DESIGN
National Institute of Standards and Technology (NIST), USA
Ram D. Sriram is currently the chief of the Software and Systems Division, Information Technology Laboratory, at the National Institute of Standards and Technology. Before joining the Software and Systems Division, Sriram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Laboratory, where he conducted research on standards for interoperability of computer-aided design systems. Prior to joining NIST, he was on the engineering faculty (1986-1994) at the Massachusetts Institute of Technology (MIT) and was instrumental in setting up the Intelligent Engineering Systems Laboratory. Sriram has co-authored or authored more than 275 publications, including several books. Sriram was a founding co-editor of the International Journal for AI in Engineering. Sriram received several awards including: an NSF’s Presidential Young Investigator Award (1989); ASME Design Automation Award (2011); ASME CIE Distinguished Service Award (2014); the Washington Academy of Sciences’ Distinguished Career in Engineering Sciences Award (2015); ASME CIE division’s Lifetime Achievement Award (2016); CMU CEE Lt. Col. Christopher Raible Distinguished Public Service Award (2018); IIT Madras Distinguished Alumni Award (2021). Sriram is a Fellow of AAIA, AIMBE, ASME, AAAS, IEEE, INCOSE, SMA, and Washington Academy of Sciences, a Distinguished Member (life) of ACM and Senior Member (life) AAAI. Sriram has a B.Tech. from IIT, Madras, India, and an M.S. and a Ph.D. from Carnegie Mellon University, Pittsburgh, USA.

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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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