| 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 | 350 | 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 | 287 | 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 | 225 | 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 | 174* | 2017 |
| 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 | 167 | 2020 |
| 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 | 154 | 2010 |
| 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 | 153 | 2009 |
| 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 | 142 | 2007 |
| Rapid inverse design of metamaterials based on prescribed mechanical behavior through machine learning CS Ha, D Yao, Z Xu, C Liu, H Liu, D Elkins, M Kile, V Deshpande, ZJ Kong, ... Nature Communications, 2023 | 137 | 2023 |
| 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 ASME Trans. Journal of Manufacturing Science and Engineering 129 (4), 821-831, 2007 | 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 | 98 | 2010 |
| 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 | 89 | 2021 |
| 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 | 82 | 2018 |
| 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 | 77 | 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 | 76 | 2014 |
| Augmented Time Regularized Generative Adversarial Network (ATR-GAN) for Data Augmentation in Online Process Anomaly Detection Y Li, Z Shi, C Liu, W Tian, ZJ Kong, CB Williams IEEE Transactions on Automation Science and Engineering, 2021 | 75 | 2021 |
| 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 | 70 | 2016 |
| 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 | 69 | 2011 |
| 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 | 65 | 2015 |
| Toward online layer-wise surface morphology measurement in additive manufacturing using a deep learning-based approach C Liu, RR Wang, I Ho, ZJ Kong, C Williams, S Babu, C Joslin Journal of Intelligent Manufacturing 34 (6), 2673-2689, 2023 | 63* | 2023 |
Prahalada RaoAssociate Professor, Virginia TechOverená e-mailová adresa na: vt.edu
