ASME

Journal of Computing and Information Science in Engineering

Bin 
He, Ph.D.
Bin He

Areas of Interest

ARTIFICIAL INTELLIGENCE METHODS FOR COMPUTATIONAL DESIGN
DESIGN FOR LOW CARBON FOOTPRINT
INTELLIGENT MANUFACTURING
ROBOTICS
SUSTAINABLE CAD/CAM/CAE
Shanghai University, China
Dr. Bin He is currently a Full Professor of Mechanical Engineering at Shanghai University. He received his degrees from B.S. to Ph.D. in Mechanical Engineering at Zhejiang University. He worked as a visiting professor at Georgia Institute of Technology. Currently, Dr. He is the Vice Dean of School of Mechatronics Engineering and Automation, Director of Intelligent Manufacturing for Carbon Neutral, Deputy Director of Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Director of Robotics and Intelligent Design Research Center, Shanghai University. He is now serving as Associate Editor of ASME Journal of Computing and Information Science in Engineering. Dr. He has also obtained Chinese Mechanical Industry Science and Technology Award, Shanghai Teaching Achievement Award. His areas of interest include sustainable CAD/CAM/CAE for carbon neutral, robotics, intelligent manufacturing, and artificial intelligence methods for computational design. For more information, please visit: https://www.researchgate.net/profile/Bin-He-49

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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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