Jie Shen
Applications:
Computer Science, Engineering
Methodologies:
Artificial Intelligence, Computer Vision, Computing, Machine Learning, Networks, Statistics
Relevant Projects:

NSF


Connections:

Editor-in-Chief, International Journal of Modelling and Simulation

Jie Shen

Professor

Computer and Information Science

Professor of Computer and Information Science, College of Engineering and Computer Science, The University of Michigan-Dearborn

One of my research interests is in the digital diagnosis of material damage based on sensors, computational science and numerical analysis with large-scale 3D computed tomography data: (1) Establishment of a multi-resolution transformation rule of material defects. (2) Design of an accurate digital diagnosis method for material damage. (3) Reconstruction of defects in material domains from X-ray CT data . (4) Parallel computation of materials damage. My team also conducted a series of studies for improving the quality of large-scale laser scanning data in reverse engineering and industrial inspection: (1) Detection and removal of non-isolated Outlier Data Clusters (2) Accurate correction of surface data noise of polygonal meshes (3) Denoising of two-dimensional geometric discontinuities.

Another research focus is on the information fusion of large-scale data from autonomous driving. Our research is funded by China Natural Science Foundation with focus on (1) laser-based perception in degraded visual environment, (2) 3D pattern recognition with dynamic, incomplete, noisy point clouds, (3) real-time image processing algorithms in degraded visual environment, and (4) brain-computer interface to predict the state of drivers.

Processing and Analysis of 3D Large-Scale Engineering Data

Processing and Analysis of 3D Large-Scale Engineering Data