Journal of Computing and Information Science in Engineering

Smith, Ph.D.
Shana Smith

Areas of Interest

National Taiwan University
Dr. Shana S. Smith holds the position of Professor in the Department of Mechanical Engineering at National Taiwan University. Before joining National Taiwan University, Dr. Smith served as an Associate Professor in the Department of Agricultural and Biosystems Engineering at Iowa State University. Prior to her tenure at Iowa State University, she worked as an Assistant Professor in the Department of Mechanical Engineering at Hong Kong University of Science and Technology. Dr. Smith’s teaching and research areas of expertise encompass haptic technology, human-computer interaction, user-centered design, and extended reality.  During her academic career, Dr. Smith was designated as a Miller Fellow for the year 2002-2003 at Iowa State University. She also served as the PI for a US National Science Foundation (NSF)-funded project aimed at enhancing undergraduate design and graphics courses using low-cost virtual reality technology. Dr. Smith was listed among the top 2% scientists worldwide in two categories: career-long impact (1960-2021) and single recent year impact (2021). This acknowledgment comes from the “September 2022 data-update for ‘Updated science-wide author databases of standardized citation indicators'” available through Elsevier Data Repository, V5.

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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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