Kamran Paynabar, Ph.D.

Affiliations: 
2012 University of Michigan, Ann Arbor, Ann Arbor, MI 
Area:
Industrial Engineering, Statistics
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"Kamran Paynabar"

Parents

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Judy Jin grad student 2012 University of Michigan
 (Nonlinear Profile Data Analysis for System Performance Improvement.)
Jionghua Jin grad student 2012 University of Michigan (Computer Science Tree)
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Publications

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Aydemir G, Paynabar K. (2020) Image-Based Prognostics Using Deep Learning Approach Ieee Transactions On Industrial Informatics. 16: 5956-5964
Gahrooei MR, Paynabar K, Pacella M, et al. (2020) Process Modeling and Prediction With Large Number of High-Dimensional Variables Using Functional Regression Ieee Transactions On Automation Science and Engineering. 17: 684-696
Gahrooei MR, Yan H, Paynabar K, et al. (2020) Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes With Heterogeneous Sources of Data Technometrics. 1-23
Peters B, Yildirim M, Gebraeel N, et al. (2020) Severity-based diagnosis for vehicular electric systems with multiple, interacting fault modes Reliability Engineering & System Safety. 195: 106605
Yan H, Paynabar K, Pacella M. (2019) Structured Point Cloud Data Analysis Via Regularized Tensor Regression for Process Modeling and Optimization Technometrics. 61: 385-395
Gorgannejad S, Reisi Gahrooei M, Paynabar K, et al. (2019) Quantitative prediction of the aged state of Ni-base superalloys using PCA and tensor regression Acta Materialia. 165: 259-269
Wang Y, Mei Y, Paynabar K. (2018) Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring Technometrics. 60: 360-372
Yan H, Paynabar K, Shi J. (2018) Real-Time Monitoring of High-Dimensional Functional Data Streams via Spatio-Temporal Smooth Sparse Decomposition Technometrics. 60: 181-197
Rahmandad H, Jalali MS, Paynabar K. (2017) A flexible method for aggregation of prior statistical findings. Plos One. 12: e0175111
Yan H, Paynabar K, Shi J. (2017) Anomaly Detection in Images With Smooth Background via Smooth-Sparse Decomposition Technometrics. 59: 102-114
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