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Yiming Deng

Professor · College of Engineering

Michigan State University · United States
NDE for Advanced ManufacturingNDE 4.0 and 5.0

简介

Yiming Deng is a Professor of ECE at NDEL, MSU. A Fellow of ASNT, Prof. Deng has extensive experience in sensors and sensing systems for nondestructive evaluation (NDE) and systems health monitoring (SHM). His current research interests include NDE for Advanced Manufacturing, NDE 4.0 and 5.0, AI-enabled NDE/SHM systems with Uncertainty Quantification (UQ), and Statistical Methods in NDE (Causal Inference, Learning). He is interested in developing novel NDE/SHM sensors and sensing systems that involve multi-physics simulations for better understanding of imaging physics and conducting experimental validation as well as sensor prototyping for a wide range of engineering applications to assure critical energy and transportation infrastructures safety, security, reliability and sustainability.

教育经历

  • Ph.D., Electrical Engineering, Michigan State University, 2009
  • B.E., Electrical Engineering, Tsinghua University, Beijing, China, 2003

代表成果

  • S. Mukherjee**, L. Udpa, Y. Deng*, Enhanced Defect Detection in NDE Using Registration aided Heterogeneous Data Fusion, NDT & E International, in press, (2023)
  • G Piao**, J Mateus, J Li, R Pachha, P Walia, Y Deng, S Chakrapani, Phased array ultrasonic imaging and characterization of adhesive bonding between thermoplastic composites aided by machine learning, Nondestructive Testing and Evaluation, DOI: 10.1080/10589759.2022.2134365, (2023)
  • Q Hu, W Lu, Y Guo, W He, H Luo, Y Deng, Vigor Detection for Naturally Aged Soybean Seeds Based on Polarized Hyperspectral Imaging Combined with Ensemble Learning Algorithm, Agriculture, 13(8), 1499, (2023)
  • S Aenagandula, S Mukherjee**, N Rao*, Y Deng, Adaptive segmentation-based evaluation of material properties of dielectric sheets using microwave NDE, Nondestructive Testing and Evaluation, 1-15, (2023)
  • A. Mohand**, Z Li**, A Rao**, J Li**, P Fairchild, X Tan, Y Deng*, IMU-assisted robotic structured light sensing with featureless registration under uncertainties for pipeline inspection, NDT & E International, 139, 102936, (2023)

数据校验于 9/6/2026数据来源

学生评价

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