| Multifidelity surrogate based on single linear regression Y Zhang, NH Kim, C Park, RT Haftka AIAA Journal 56 (12), 4944-4952, 2018 | 84 | 2018 |
| Advances in bayesian probabilistic modeling for industrial applications S Ghosh, P Pandita, S Atkinson, W Subber, Y Zhang, NC Kumar, ... ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2020 | 30 | 2020 |
| General Surrogate Adaptive Sampling using Interquartile Range for Design Space Exploration Y Zhang, NH Kim, RT Haftka AIAA Scitech 2019 Forum, 2213, 2019 | 26 | 2019 |
| A strategy for adaptive sampling of multi-fidelity gaussian processes to reduce predictive uncertainty S Ghosh, J Kristensen, Y Zhang, W Subber, L Wang International Design Engineering Technical Conferences and Computers and …, 2019 | 21 | 2019 |
| Mechanical performance of triply periodic minimal surface structures with a novel hybrid gradient fabricated by selective laser melting N Qiu, J Zhang, F Yuan, Z Jin, Y Zhang, J Fang Engineering Structures 263, 114377, 2022 | 17 | 2022 |
| Industrial applications of intelligent adaptive sampling methods for multi-objective optimization J Kristensen, W Subber, Y Zhang, S Ghosh, NC Kumar, G Khan, L Wang Design and Manufacturing, 2019 | 16 | 2019 |
| Remarks for scaling up a general gaussian process to model large dataset with sub-models Y Zhang, S Ghosh, P Pandita, W Subber, G Khan, L Wang AIAA Scitech 2020 Forum, 0678, 2020 | 10 | 2020 |
| Function prediction at one inaccessible point using converging lines Y Zhang, C Park, NH Kim, RT Haftka Journal of Mechanical Design 139 (5), 051402, 2017 | 10 | 2017 |
| On approaches to combine experimental strength and simulation with application to open-hole-tension configuration Y Zhang, J Meeker, J Schutte, N Kim, R Haftka Proceedings of the American Society for composites: thirty-first technical …, 2016 | 10 | 2016 |
| Learning uncertainty using clustering and local gaussian process regression Y Zhang, S Ghosh, I Asher, Y Ling, L Wang AIAA Scitech 2019 Forum, 1730, 2019 | 8 | 2019 |
| Multi-fidelity surrogate modeling for application/architecture co-design Y Zhang, A Neelakantan, N Kumar, C Park, RT Haftka, NH Kim, H Lam High Performance Computing Systems. Performance Modeling, Benchmarking, and …, 2018 | 8 | 2018 |
| Predicting B-basis allowable at untested points from experiments and simulations of plates with holes Y Zhang, J Schutte, J Meeker, U Palliyaguru, NH Kim, RT Haftka 12th World Congress on Structural and Multidisciplinary Optimization …, 2017 | 8 | 2017 |
| Finding maximum expected improvement for high-dimensional design optimization Y Zhang, J Kristensen, S Ghosh, T Vandeputte, J Tallman, L Wang AIAA Aviation 2019 Forum, 2985, 2019 | 7 | 2019 |
| Probabilistic machine learning assisted feature-based qualification of DED Ti64 S Nag, Y Zhang, S Karnati, L Kerwin, A Kitt, E MacDonald, D Cheung, ... JOM 73 (10), 3064-3081, 2021 | 6 | 2021 |
| Adaptive sampling with varying sampling cost for design space exploration Y Zhang, A Neelakantan, C Park, NH Kim, H Lam, RT Haftka AIAA Journal 57 (3), 1032-1043, 2019 | 6 | 2019 |
| Reduced allowable strength of composite laminate for unknown distribution due to limited tests Y Zhang, NH Kim, UR Palliyaguru, JF Schutte, RT Haftka Journal of Composite Materials 54 (21), 2823-2836, 2020 | 5 | 2020 |
| Sampling by exploration and replication for estimating experimental strength of composite structures Y Zhang, JF Schutte, WP Seneviratne, NH Kim, RT Haftka AIAA Journal 55 (10), 3594-3602, 2017 | 5 | 2017 |
| Allocation of samples between exploration and replication for open-hole-tension test Y ZHANG, RT HAFTKA, NAMHO KIM, JF SCHUTTE, WP SENEVIRATNE American Society of Composites-30th Technical Conference, 2015 | 5 | 2015 |
| One-dimensional Function Extrapolation Using Surrogates RTH Yiming Zhang, Nam-Ho Kim., Chanyoung Park 11th World Congress on Structural and Multidisciplinary Optimization, 2015 | 5* | 2015 |
| Accelerating Additive Design With Probabilistic Machine Learning Y Zhang, S Karnati, S Nag, N Johnson, G Khan, B Ribic ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2022 | 4 | 2022 |
