| Online Real-Time Quality Monitoring in Additive Manufacturing Processes Using Heterogeneous Sensors PK Rao, JP Liu, D Roberson, ZJ Kong, C Williams ASME Trans. Journal of Manufacturing Science and Engineering 137 (6), 061007, 2015 | 313 | 2015 |
| Time Series Forecasting for Nonlinear and Non-Stationary Processes: a Review and Comparative Study C Cheng, A Sa-Ngasoongsong, O Beyca, T Le, H Yang, ZJ Kong, ... IISE Transactions 47 (10), 1053-1071, 2015 | 233 | 2015 |
| Image Analysis-based Closed Loop Quality Control for Additive Manufacturing with Fused Filament Fabrication C Liu, A Law, DM Roberson, ZJ Kong Journal of Manufacturing Systems 51, 75-86, 2019 | 178 | 2019 |
| Classifying the Dimensional Variation in Additive Manufactured Parts from Laser-Scanned 3D Point Cloud Data using Machine Learning Approaches MS Tootooni, A Dsouza, R Donovan, PK Rao, ZJ Kong, P Borgesen ASME Trans. Journal of Manufacturing Science and Engineering 139 (9), 091005, 2017 | 154* | 2017 |
| UseLearn: A novel checklist and usability evaluation method for eLearning systems by criticality metric analysis A Oztekin, ZJ Kong, O Uysal International Journal of Industrial Ergonomics 40 (4), 455-469, 2010 | 149 | 2010 |
| Stream-of-variation (SOVA) modeling II: a generic 3D variation model for rigid body assembly in multistation assembly processes W Huang, J Lin, ZJ Kong, D Ceglarek ASME Trans. Journal of manufacturing science and engineering 129 (4), 832-842, 2007 | 146 | 2007 |
| Predicting the graft survival for heart–lung transplantation patients: an integrated data mining methodology A Oztekin, D Delen, ZJ Kong International journal of medical informatics 78 (12), e84-e96, 2009 | 145 | 2009 |
| In situ investigation into temperature evolution and heat generation during additive friction stir deposition: A comparative study of Cu and Al-Mg-Si D Garcia, WD Hartley, HA Rauch, RJ Griffiths, R Wang, ZJ Kong, Y Zhu, ... Additive Manufacturing 34, 101386, 2020 | 117 | 2020 |
| Stream-of-variation modeling—Part I: A generic three-dimensional variation model for rigid-body assembly in single station assembly processes W Huang, J Lin, M Bezdecny, Z Kong, D Ceglarek | 109 | 2007 |
| A Machine Learning-based Approach to Prognostic Analysis of Thoracic Transplantations D Delen, A Oztekin, ZJ Kong Artificial Intelligence in Medicine 49 (1), 33-42, 2010 | 92 | 2010 |
| An Online Sparse Estimation-based Classification Approach for Real-time Monitoring in Advanced Manufacturing Processes from Heterogeneous Sensor Data K Bastani, P Rao, ZJ Kong IISE Transaction 48 (7), 579-598, 2016 | 72 | 2016 |
| Real-Time Identification of Incipient Surface Morphology Variations in Ultraprecision Machining Process P Rao, S Bukkapatnam, O Beyca, ZJ Kong, R Komanduri ASME Trans. Journal of Manufacturing Science and Engineering 136 (2), 021008, 2014 | 70 | 2014 |
| A robust ensemble-deep learning model for COVID-19 diagnosis based on an integrated CT scan images database M Maftouni, ACC Law, B Shen, ZJ Kong, Y Zhou, NA Yazdi IISE Annual Conference and Expo, 632-637, 2021 | 66 | 2021 |
| Development of a structural equation modeling-based decision tree methodology for the analysis of lung transplantations A Oztekin, ZJ Kong, D Delen Decision Support Systems 51 (1), 155-166, 2011 | 65 | 2011 |
| Additive manufacturing of pharmaceuticals for precision medicine applications: A review of the promises and perils in implementation M Trivedi, J Jee, S Silva, C Blomgren, VM Pontinha, DL Dixon, ... Additive Manufacturing 23, 319-328, 2018 | 64 | 2018 |
| Online non-contact surface finish measurement in machining using graph theory-based image analysis MS Tootooni, C Liu, D Roberson, R Donovan, PK Rao, ZJ Kong, ... Journal of Manufacturing Systems 41, 266-276, 2016 | 63 | 2016 |
| Assessment of Dimensional Integrity and Spatial Defect Localization in Additive Manufacturing (AM) using Spectral Graph Theory (SGT) P Rao, ZJ Kong, C Duty, R Smith, V Kunc, L Love ASME Trans. Journal of Manufacturing Science and Engineering, 2015 | 60 | 2015 |
| A graph-theoretic approach for quantification of surface morphology variation and its application to chemical mechanical planarization process PK Rao, OF Beyca, ZJ Kong, STS Bukkapatnam, KE Case, R Komanduri IISE Transactions 47 (10), 1088-1111, 2015 | 58 | 2015 |
| Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory OF Beyca, PK Rao, ZJ Kong, STS Bukkapatnam, R Komanduri IEEE Trans. on Automation Science and Engineering, 2015 | 55 | 2015 |
| Process performance prediction for chemical mechanical planarization (CMP) by integration of nonlinear Bayesian analysis and statistical modeling ZJ Kong, A Oztekin, OF Beyca, U Phatak, STS Bukkapatnam, ... IEEE Transactions on Semiconductor Manufacturing 23 (2), 316-327, 2010 | 52 | 2010 |
Prahalada RaoAssociate Professor, Virginia TechVerified email at vt.edu
