Kamran Paynabar

Fouts Family Chair and Professor in the Stewart School of Industrial & Systems Engineering

Publications

JOURNAL PUBLICATIONS 

  1. *Yan, H., Paynabar, K., Shi, J., (2019) “AKM2D: An Adaptive Framework for Online Sensing and Anomaly Detection,” IISE Transactions on Quality and Reliability Engineering, (Accepted). INFORMS QSR Best Student Paper Finalist (2016).
  2. *Reisi, M., *Yan, H., Paynabar, K., Shi, J., (2019) “Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes with Heterogeneous Sources of Data,” Technometrics (Accepted). INFORMS Data Mining Best Student Paper Winner (2016).
  3. *Aydemir, G., Paynabar, K., (2019) “Image-based Prognostics Using Deep Learning Approach”, IEEE Transactions on Industrial Informatics (Accepted).
  4. *Reisi, M., *Yan, H., Paynabar, K., Shi, J., (2019) Discussion on “On Active Learning Methods for Manifold Data (Accepted).
  5. *Peters B., *Yildirim M., Gebraeel N. and Paynabar K., (2019) “Severity-based Diagnostics for Vehicular Electric Systems with Multiple Interacting Fault Modes”, Reliability Engineering and Systems Safety (Accepted).
  6. *Reisi, M., Paynabar K., Pacella, M., Colosimo, B. (2019), An adaptive fused sampling approach of high-accuracy data in the presence of low-accuracy data. IIE Transactions on Quality and Reliability Engineering, Vol. 51, pp. 1251-1264.
  7. Gorgan Nejad, S., *Reisi, M., Paynabar, K., Neu, R., (2019) “Quantitative prediction of the aged state of Ni-base superalloys using PCA and tensor regression,” Acta Materialia, Vol. 165, pp.259-269.
  8. *Fang, X., Paynabar, K., Gebraeel, N., (2019) “Residual Useful Lifetime Prediction Using a Degradation Image Stream via Penalized Tensor ” Technometrics, Vol. 61, pp. 369-384. INFORMS Best QSR Paper Finalist (2016) and INFORMS Data Mining Best Paper Winner (2016).
  1. *Yan, H., Paynabar, K., Pacella, M., (2019) “Point Cloud Data Analysis for Process Modeling and Optimization”, Technometrics, 61, pp. 385-395.
  2. *Reisi, M., Paynabar, K., Shi, J., (2019) “Process Modeling and Prediction with High-Dimensional Variables Using Functional Regression”, IEEE Transactions on Automation Science and Engineering, (Accepted).
  3. Jafari-Khouzani, K., Paynabar, K., Rosen, B., (2019) “Effect of Region of Interest Size on the Repeatability of Quantitative Brain Imaging Biomarkers”, IEEE Transactions on Biomedical Eng., Vol. 66, pp. 864 – 872.
  4. *Wang, Y., Mei, Y., Paynabar, K. (2018) “Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring”, Technometrics, Vol. 60, pp. 360-372.
  5. *Reisi, M., Paynabar, K., (2018) “Change Detection in a Dynamic Stream of Attributed Networks”, Journal of Quality Technology, Vol. 50, pp. 418-430.
  6. *Ranjan C., Paynabar, K., Reuter, M., Jafari-Khouzani, K., (2018) “Longitudinal MRI data analysis in presence of measurement error but absence of replicates”, IIE Transactions on Healthcare Systems Engineering, Vol.8, pp. 117-130.
  7. *Ranjan C., Paynabar, K., Helm, J., Pan J. (2017) “The Impact of Estimation: A New Method for Clustering and Trajectory Estimation in Patient Flow Modeling”, Production and Operations Management, Vol. 26, pp.1893-1914. POMS Best Paper Award – College of Healthcare Operations Management (2015).
  1. *Yan, H., Paynabar, K., Shi, J., (2017) “Real-time Monitoring of High-Dimensional Functional Data Streams via Spatio-Temporal Smooth Sparse Decomposition,” Technometrics, Vol. 60, pp.181-197. INFORMS Best QSR Paper Award (2015) and ISERC QCRE Best Student Paper Award (2015).
  1. *Fang, X., Gebraeel, N., Paynabar, K., (2017) “Scalable prognostic models for large-scale condition monitoring applications,” IIE Transactions on Quality and Reliability Engineering, Vol. 49, pp.698-710. Featured in IIE Magazine.
  1. *Yan, H., Paynabar, K., Shi, J., (2015) “Anomaly Detection in Images with Smooth Background Via Smooth-Sparse Decomposition,” Technometrics, Vo. 59, pp. 102-104. INFORMS Data Mining Best Student Paper Award (2014).
  1. *Rahmandad H., Jalali M., Paynabar, K., (2017) “A Flexible Method for Aggregation of Prior Statistical Findings”. PLoS ONE, 12, Issue 4.
  2. *Woodall, W. H., Zhao, M., Paynabar, K., Sparks, R., and Wilson, J. D. (2017). “An Overview and Perspective on Social Network Monitoring”, IIE Transactions on Quality and Reliability Engineering, Vol. 49, pp. 354-365.
  3. *Fang, X., Paynabar, K., Gebraeel, N., (2017) “Multistream Sensor Fusion Based Prognostics Model for Systems with Single Failure Modes.” Reliability Engineering and Systems Safety, Vol. 159, pp. 322-331.
  4. *Mesnil O., Yan, H., Ruzzene M., Paynabar, K., Shi J., (2016) “Fast Wavenumber Measurement for Accurate and Automatic Location and Quantification of Defect in Composite”, Structural Health Monitoring, Vol. 15, pp. 223–234.
  5. *Masoud, H., Reed, M. P., Paynabar, K., Wang N., Jin, J., Wan J., Kozak K. K., Gomez-Levi, G. (2016) “Predicting Subjective Responses from Human Motion: Application to Vehicle Ingress Assessment,” ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 138, Issue 6, 061001-061001-8.
  6. Guo, W., Paynabar, K., Jin, J., Miller, B., Carpenter, J., (2015) “A Decision Support System on Surgical Treatments for Rotator Cuff Tears”, IIE Transactions on Healthcare Systems Engineering, 5, Issue 3, pp. 197-210. Featured in IIE Magazine.
  1. *Paynabar, K., Peihua, Q., and Zou C., (2016) “A Change Point Approach for Phase-I Analysis in Multivariate Profiles Monitoring and Diagnosis,” Technometrics, Vo. 58, Issue 2, pp. 191-204.
  2. *Azarnoush, B., Paynabar K., Bekki, J., Runger G., (2016) “Monitoring Temporal Homogeneity in Network Streams,” Journal of Quality Technology, Vol. 48, pp. 28–43.
  3. *Jafari-Khouzani, K., Emblem, E., Kalpathy-Cramer, K., Bjørnerud, A., Vangel, M., Gerstner, E., Schmainda K., Paynabar K., Batchelor, T., Wen, P., Rosen, B., Stufflebeam, S., (2015) “Repeatability of cerebral perfusion measurements using susceptibility contrast MRI,” Translational Oncology, 8, Issue 3, pp. 137–146.
  4. *Yan, H., Paynabar, K., Shi, J., (2015) “Image-Based Process Monitoring Using Low Rank Tensor Decomposition,” IEEE Transactions on Automation Science and Engineering, Vol. 12, Issue 1, pp. 216-227.
  5. Paynabar, K., Jin, J., and M. Reed, (2015) “Hierarchical Non-Negative Garrote for Group Variable Selection,” Technometrics, Vol. 57, Issue 4, pp. 514 – 523. INFORMS Data Mining Best Student Paper Award (2011).
  1. Paynabar, K., Jin, J., and M. Pacella, (2013) “Monitoring and Diagnosis of Multichannel Nonlinear Profile Variations Using Uncorrelated Multilinear Principal Component Analysis,” IIE Transactions on Quality and Reliability Engineering, Vol. 45, 1235-1247.
  2. Shao, C., Paynabar, K., Kim, T., Jin J., Hu, J., Spicer, P., Wang H., and Abell, J., (2013) “Feature Selection for Manufacturing Process Monitoring Using Cross-Validation,” Journal of Manufacturing Systems, Vol. 32, Issue 4, pp. 550–555.
  3. Paynabar, K., Jin, J., Agapiou, J., and Deeds, P. (2012) “Robust Leak Tests for Transmission Systems Using Nonlinear Mixed-Effect Models,” Journal of Quality Technology, 44, 265–278.
  4. Paynabar, K., Jin, J., and Yeh. B. A. (2012) “Phase I Risk-Adjusted Control Charts for Monitoring Surgical Performance by Considering Categorical Covariates,” Journal of Quality Tech., Vol. 44, 39-53.
  5. Guo, H., Paynabar, K., and Jin, J. (2011) “Multiscale Monitoring of Autocorrelated Processes Using Wavelets Analysis,” IIE Transactions on Quality and Reliability Engineering, 44, 312-326.
  6. Paynabar, K., Jin, J. (2011) “Characterization of Nonlinear Profiles Variations using Mixed-effect Models and Wavelets,” IIE Transactions on Quality and Reliability Engineering, Vol. 43, 275–290. Best Application Paper Award from IIE Transactions (2011). Richard C. Wilson Prize for Best Student Paper in Manufacturing Systems, The University of Michigan (2010).
  1. Abad, A., Paynabar, K., and Jin, J. (2011) “Modeling and Analysis of Operators Effect on Process Quality and Throughput in Mixed Model Assembly Systems,” ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 133, 021016-021016-9.
  2. Lei, Y., Paynabar, K., Jin, J. and Agapiou, J. (2009) “Cyclic Waveform Signal Analysis for Online Monitoring of Valve Seat Assembly Processes,” Transactions of the NAMRI/SME, 2009, Vol. 37. 459-466.
  3. Noorossana, R., Saghaei, A., Paynabar, K., and Abdi, S. (2009) “Identifying the Time of a Change in High Quality Processes,” Quality and Reliability Engineering International Journal. 25, 875–883.
  4. Noorossana, R., Saghaei, A., Paynabar, K., and Samimi, Y., (2007) “On the Conditional Decision Procedure for High Yield Processes,” Computers and Industrial Engineering. Vol. 53, 469–477.

SUBMITTED

  1. *Ranjan, C., *Ebrahimi, S., Paynabar, K., “Sequence Graph Transform (SGT): A Feature Extraction Function for Sequence Data Mining”, (Under review).
  2. Estrada Gomez, A.M., Paynabar, K., Pacella, M., “Functional Directed Graphical Models and Applications in Root-Cause Analysis and Diagnosis”, (Under review).
  3. *Ebrahimi, S., *Ranjan, C., Paynabar, K., “Large Multistream Data Analytics for Systems Monitoring and Diagnostics”, (Under review).
  4. *Ebrahimi, S., *Reisi, M., Paynabar, K., Mankad S. “Monitoring Financial Networks with Online Hurdle Models”, (Under review).
  5. *Fang, X., *Yan, H., Gebraeel, N., Paynabar, K., “Multi-Sensor Prognostic Modeling for Applications with Highly Incomplete Signals”, (Under review).

REFEREED CONFERENCE PROCEEDINGS

  1. *Mesnil O., Yan, H., Ruzzene M., Paynabar, K., Shi J., (2015) “Guided Wavefield Reconstruction from Sparse Measurements Using Compressed Sensing,” 10th International Workshop on Structural Health Monitoring, Stanford, CA.
  2. *Mesnil, Yan, H., Ruzzene M., Paynabar, K., Shi J., (2014) “Frequency Domain InstantaneousWavenumber Estimation for Damage Quantification in Layered Plate Structures,” 7th European Workshop on Structural Health Monitoring, Nantes, France.
  3. Aminnayeri, M., Noorossana, R., Haghighi, M., and Paynabar, K., (2007) “Economic Statistical Design of T2 Control Charts for Systems with Gamma In-control Times,” 37th International Conference on Computers and Industrial Eng., Egypt.
  4. Aminnayeri M., Paynabar, K., and Arbabzade N., (2005) “Designing Geometric Zone Control Charts in High Quality Processes,” 35th International Conference on Computers and Industrial Eng., Turkey.

*The author is/was a graduate student at Georgia Tech .