On the conditional decision procedure for high yield processes. - Rassoul Noorossana; Abbas Saghaei; Kamran Paynabar; Yaser Samimi (Comput. Ind. Eng., 2007)

Identifying the period of a step change in high-yield processes. - Rassoul Noorossana; Abbas Saghaei; Kamran Paynabar; Sara Abdi (Qual. Reliab. Eng. Int., 2009)

Image-Based Process Monitoring Using Low-Rank Tensor Decomposition. - Hao Yan; Kamran Paynabar; Jianjun Shi 001 (IEEE Trans Autom. Sci. Eng., 2015)

Informative Sensor and Feature Selection via Hierarchical Nonnegative Garrote. - Kamran Paynabar; Judy Jin; Matthew P. Reed (Technometrics, 2015)

Sequence Graph Transform (SGT): A Feature Extraction Function for Sequence Data Mining. - Chitta Ranjan; Samaneh Ebrahimi 001; Kamran Paynabar (CoRR, 2016)

An overview and perspective on social network monitoring. - William H. Woodall; Meng J. Zhao; Kamran Paynabar; Ross Sparks; James D. Wilson (CoRR, 2016)

A Change-Point Approach for Phase-I Analysis in Multivariate Profile Monitoring and Diagnosis. - Kamran Paynabar; Changliang Zou; Peihua Qiu (Technometrics, 2016)

Multistream sensor fusion-based prognostics model for systems with single failure modes. - Xiaolei Fang; Kamran Paynabar; Nagi Gebraeel (Reliab. Eng. Syst. Saf., 2017)

Anomaly Detection in Images With Smooth Background via Smooth-Sparse Decomposition. - Hao Yan; Kamran Paynabar; Jianjun Shi 001 (Technometrics, 2017)

Dataset: Rare Event Classification in Multivariate Time Series. - Chitta Ranjan; Markku Mustonen; Kamran Paynabar; Karim Pourak (CoRR, 2018)

Large Multistream Data Analytics for Monitoring and Diagnostics in Manufacturing Systems. - Samaneh Ebrahimi 001; Chitta Ranjan; Kamran Paynabar (CoRR, 2018)

Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring. - Yuan Wang 007; Yajun Mei; Kamran Paynabar (Technometrics, 2018)

Real-Time Monitoring of High-Dimensional Functional Data Streams via Spatio-Temporal Smooth Sparse Decomposition. - Hao Yan; Kamran Paynabar; Jianjun Shi 001 (Technometrics, 2018)

AKM2D : An Adaptive Framework for Online Sensing and Anomaly Quantification. - Hao Yan; Kamran Paynabar; Jianjun Shi (CoRR, 2019)

An adaptive fused sampling approach of high-accuracy data in the presence of low-accuracy data. - Mostafa Reisi Gahrooei; Kamran Paynabar; Massimo Pacella; Bianca Maria Colosimo (IISE Trans., 2019)

Effect of Region of Interest Size on the Repeatability of Quantitative Brain Imaging Biomarkers. - Kourosh Jafari-Khouzani; Kamran Paynabar; Fatemeh Hajighasemi; Bruce R. Rosen (IEEE Trans. Biomed. Eng., 2019)

Image-Based Prognostics Using Penalized Tensor Regression. - Xiaolei Fang; Kamran Paynabar; Nagi Gebraeel (Technometrics, 2019)

Structured Point Cloud Data Analysis Via Regularized Tensor Regression for Process Modeling and Optimization. - Hao Yan; Kamran Paynabar; Massimo Pacella (Technometrics, 2019)

Deep Learning Based Covert Attack Identification for Industrial Control Systems. - Dan Li 030; Paritosh Ramanan; Nagi Gebraeel; Kamran Paynabar (ICMLA, 2020)

Multi-Robot Coordination for Estimation and Coverage of Unknown Spatial Fields. - Alessia Benevento; María Santos 003; Giuseppe Notarstefano; Kamran Paynabar; Matthieu R. Bloch; Magnus Egerstedt (ICRA, 2020)

Real-time Detection of Clustered Events in Video-imaging data with Applications to Additive Manufacturing. - Hao Yan; Marco Grasso; Kamran Paynabar; Bianca Maria Colosimo (CoRR, 2020)

AKM2D: An adaptive framework for online sensing and anomaly quantification. - Hao Yan; Kamran Paynabar; Jianjun Shi 001 (IISE Trans., 2020)

Severity-based diagnosis for vehicular electric systems with multiple, interacting fault modes. - Benjamin Peters; Murat Yildirim; Nagi Gebraeel; Kamran Paynabar (Reliab. Eng. Syst. Saf., 2020)

Process Modeling and Prediction With Large Number of High-Dimensional Variables Using Functional Regression. - Mostafa Reisi Gahrooei; Kamran Paynabar; Massimo Pacella; Jianjun Shi 001 (IEEE Trans Autom. Sci. Eng., 2020)

Image-Based Prognostics Using Deep Learning Approach. - Gürkan Aydemir; Kamran Paynabar (IEEE Trans. Ind. Informatics, 2020)

An Online Approach to Cyberattack Detection and Localization in Smart Grid. - Dan Li 030; Nagi Gebraeel; Kamran Paynabar; A. P. Sakis Meliopoulos (CoRR, 2021)

Multi-Objective Allocation of COVID-19 Testing Centers: Improving Coverage and Equity in Access. - Zhen Zhong; Ribhu Sengupta; Kamran Paynabar; Lance A. Waller (CoRR, 2021)

Multi-sensor prognostics modeling for applications with highly incomplete signals. - Xiaolei Fang; Hao Yan; Nagi Gebraeel; Kamran Paynabar (IISE Trans., 2021)

A degradation-based detection framework against covert cyberattacks on SCADA systems. - Dan Li 030; Kamran Paynabar; Nagi Gebraeel (IISE Trans., 2021)

Detection and Differentiation of Replay Attack and Equipment Faults in SCADA Systems. - Dan Li 030; Nagi Gebraeel; Kamran Paynabar (IEEE Trans Autom. Sci. Eng., 2021)

Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes With Heterogeneous Sources of Data. - Mostafa Reisi Gahrooei; Hao Yan; Kamran Paynabar; Jianjun Shi 001 (Technometrics, 2021)

Robust Feature Learning for Remaining Useful Life Estimation Using Siamese Neural Networks. - Gürkan Aydemir; Kamran Paynabar; Burak Acar (EUSIPCO, 2022)

Sequence graph transform (SGT): a feature embedding function for sequence data mining. - Chitta Ranjan; Samaneh Ebrahimi 001; Kamran Paynabar (Data Min. Knowl. Discov., 2022)

Monitoring sparse and attributed networks with online Hurdle models. - Samaneh Ebrahimi 001; Mostafa Reisi Gahrooei; Kamran Paynabar; Shawn Mankad (IISE Trans., 2022)

Online detection of cyber-incidents in additive manufacturing systems via analyzing multimedia signals. - Wei Yang 056; Jialei Chen 002; Chuck Zhang; Kamran Paynabar (Qual. Reliab. Eng. Int., 2022)

An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-Dimensional Streaming Data. - Ana María Estrada Gómez; Dan Li 030; Kamran Paynabar (Technometrics, 2022)

Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data. - Qian Wang 035; Kamran Paynabar (CoRR, 2023)

A Novel Two-level Causal Inference Framework for On-road Vehicle Quality Issues Diagnosis. - Qian Wang 035; Huanyi Shui; Thi Tu Trinh Tran; Milad Zafar Nezhad; Devesh Upadhyay; Kamran Paynabar; Anqi He (CoRR, 2023)

Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling. - Upala Junaida Islam; Kamran Paynabar; George Runger; Ashif Sikandar Iquebal (CoRR, 2023)

A tensor-based hierarchical process monitoring approach for anomaly detection in additive manufacturing. - Wei Yang 056; Marco Grasso; Bianca Maria Colosimo; Kamran Paynabar (Qual. Reliab. Eng. Int., 2023)

Image-Based Feedback Control Using Tensor Analysis. - Zhen Zhong; Kamran Paynabar; Jianjun (Jan) Shi (Technometrics, 2023)

Physics-based Penalization for Hyperparameter Estimation in Gaussian Process Regression. - Jinhyeun Kim; Christopher Luettgen; Kamran Paynabar; Fani Boukouvala (Comput. Chem. Eng., 2023)

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm. - Anjolaoluwa Ayomide Popoola; Jennifer Koren Frediani; Terryl Johnson Hartman; Kamran Paynabar (BMC Medical Informatics Decis. Mak., 2023)

Stream-Based Active Learning for Process Monitoring. - Christian Capezza; Antonio Lepore; Kamran Paynabar (CoRR, 2024)

Tensor-Based Temporal Control for Partially Observed High-Dimensional Streaming Data. - Zihan Zhang; Shancong Mou; Kamran Paynabar; Jianjun Shi (Technometrics, 2024)

Sequential sampling for functional estimation via Sieve. - Alessia Benevento; Pouya Ahadi; Swati Gupta; Massimo Pacella; Kamran Paynabar (Qual. Reliab. Eng. Int., 2024)

Statistical Process Monitoring from Industry 2.0 to Industry 4.0: Insights into Research and Practice. - Bianca Maria Colosimo; L. Allison Jones-Farmer; Fadel M. Megahed; Kamran Paynabar; Chitta Ranjan; William H. Woodall (Technometrics, 2024)

smashGP: Large-Scale Spatial Modeling via Matrix-Free Gaussian Processes. - Lucas Erlandson; Ana María Estrada Gómez; Edmond Chow; Kamran Paynabar (J. Comput. Graph. Stat., 2025)

RDDPM: Robust Denoising Diffusion Probabilistic Model for Unsupervised Anomaly Segmentation. - Mehrdad Moradi; Kamran Paynabar (CoRR, 2025)

Single-Step Reconstruction-Free Anomaly Detection and Segmentation via Diffusion Models. - Mehrdad Moradi; Marco Grasso; Bianca Maria Colosimo; Kamran Paynabar (CoRR, 2025)

Tensorized Multi-Task Learning for Personalized Modeling of Heterogeneous Individuals with High-Dimensional Data. - Elif Konyar; Mostafa Reisi Gahrooei; Kamran Paynabar (CoRR, 2025)