| Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing J Li, R Jin, ZY Hang Materials & Design 139, 473-485, 2018 | 103 | 2018 |
| A review of modeling bioelectrochemical systems: engineering and statistical aspects S Luo, H Sun, Q Ping, R Jin, Z He Energies 9 (2), 111, 2016 | 89 | 2016 |
| Nonlinear general path models for degradation data with dynamic covariates Z Xu, Y Hong, R Jin Applied Stochastic Models in Business and Industry 32 (2), 153-167, 2016 | 72 | 2016 |
| Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs) Y Li, R Jin, Y Luo Journal of the American Medical Informatics Association 26 (3), 262-268, 2019 | 63 | 2019 |
| Functional quantitative and qualitative models for quality modeling in a fused deposition modeling process H Sun, PK Rao, ZJ Kong, X Deng, R Jin IEEE Transactions on Automation Science and Engineering 15 (1), 393-403, 2017 | 53 | 2017 |
| Sequential measurement strategy for wafer geometric profile estimation R Jin, CJ Chang, J Shi Iie transactions 44 (1), 1-12, 2012 | 52 | 2012 |
| Quality modeling of printed electronics in aerosol jet printing based on microscopic images H Sun, K Wang, Y Li, C Zhang, R Jin Journal of Manufacturing Science and Engineering 139 (7), 071012, 2017 | 48 | 2017 |
| QQ models: Joint modeling for quantitative and qualitative quality responses in manufacturing systems X Deng, R Jin Technometrics 57 (3), 320-331, 2015 | 45 | 2015 |
| Reconfigured piecewise linear regression tree for multistage manufacturing process control R Jin, J Shi IIE Transactions 44 (4), 249-261, 2012 | 45 | 2012 |
| PDE-constrained Gaussian process model on material removal rate of wire saw slicing process H Zhao, R Jin, S Wu, J Shi | 45 | 2011 |
| Multimode variation modeling and process monitoring for serial-parallel multistage manufacturing processes R Jin, K Liu Iie Transactions 45 (6), 617-629, 2013 | 35 | 2013 |
| Manufacturing quality prediction using smooth spatial variable selection estimator with applications in aerosol jet® printed electronics manufacturing Y Li, H Sun, X Deng, C Zhang, HP Wang, R Jin IISE Transactions 52 (3), 321-333, 2020 | 31 | 2020 |
| Logistic regression for crystal growth process modeling through hierarchical nonnegative garrote-based variable selection H Sun, X Deng, K Wang, R Jin Iie Transactions 48 (8), 787-796, 2016 | 31 | 2016 |
| Meta-modeling of high-fidelity FEA simulation for efficient product and process design in additive manufacturing L Wang, X Chen, S Kang, X Deng, R Jin Additive Manufacturing 35, 101211, 2020 | 30 | 2020 |
| Robust fixture layout design for a product family assembled in a multistage reconfigurable line LE Izquierdo, SJ Hu, H Du, R Jin, H Jee, J Shi | 30 | 2009 |
| Ensemble modeling for data fusion in manufacturing process scale-up R Jin, X Deng IIE Transactions 47 (3), 203-214, 2015 | 29 | 2015 |
| A hierarchical model for characterising spatial wafer variations L Bao, K Wang, R Jin International Journal of Production Research 52 (6), 1827-1842, 2014 | 27 | 2014 |
| Quality prediction and control in rolling processes using logistic regression R Jin, J Li, J Shi Transactions of NAMRI/SME 35, 113-120, 2007 | 27 | 2007 |
| Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective SK Kang, R Jin, X Deng, RS Kenett Journal of Intelligent Manufacturing, 1-14, 2023 | 25 | 2023 |
| Process adjustment with an asymmetric quality loss function J Zhang, W Li, K Wang, R Jin Journal of Manufacturing Systems 33 (1), 159-165, 2014 | 25 | 2014 |