| Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation J Zhu, Y Wang, Y Huang, R Bhushan Gopaluni, Y Cao, M Heere, ... Nature communications 13 (1), 2261, 2022 | 265 | 2022 |
| An interior-point method for efficient solution of block-structured NLP problems using an implicit Schur-complement decomposition J Kang, Y Cao, DP Word, CD Laird Computers & Chemical Engineering 71, 563-573, 2014 | 58 | 2014 |
| Machine learning algorithms for liquid crystal-based sensors Y Cao, H Yu, NL Abbott, VM Zavala ACS sensors 3 (11), 2237-2245, 2018 | 55 | 2018 |
| Graph-based modeling and simulation of complex systems J Jalving, Y Cao, VM Zavala Computers & Chemical Engineering 125, 134-154, 2019 | 46 | 2019 |
| Arcobacter Identification and Species Determination Using Raman Spectroscopy Combined with Neural Networks K Wang, L Chen, X Ma, L Ma, KC Chou, Y Cao, IUH Khan, G Gölz, X Lu Applied and environmental microbiology 86 (20), e00924-20, 2020 | 38 | 2020 |
| Predicting and optimizing syngas production from fluidized bed biomass gasifiers: A machine learning approach JY Kim, D Kim, ZJ Li, C Dariva, Y Cao, N Ellis Energy 263, 125900, 2023 | 30 | 2023 |
| Multi-objective transient peak shaving optimization of a gas pipeline system under demand uncertainty Q Chen, C Wu, L Zuo, M Mehrtash, Y Wang, Y Bu, R Sadiq, Y Cao Computers & Chemical Engineering 147, 107260, 2021 | 30 | 2021 |
| Real-time feasible multi-objective optimization based nonlinear model predictive control of particle size and shape in a batch crystallization process Y Cao, D Acevedo, ZK Nagy, CD Laird Control Engineering Practice 69, 1-8, 2017 | 29 | 2017 |
| An augmented Lagrangian interior-point approach for large-scale NLP problems on graphics processing units Y Cao, A Seth, CD Laird Computers & Chemical Engineering 85, 76-83, 2016 | 29 | 2016 |
| Deep neural network approximation of nonlinear model predictive control Y Cao, RB Gopaluni IFAC-PapersOnLine 53 (2), 11319-11324, 2020 | 26 | 2020 |
| Clustering-based preconditioning for stochastic programs Y Cao, CD Laird, VM Zavala Computational optimization and applications 64, 379-406, 2016 | 26 | 2016 |
| A new global solver for transmission expansion planning with AC network model M Mehrtash, Y Cao IEEE Transactions on Power Systems 37 (1), 282-293, 2021 | 24 | 2021 |
| Multiscale model predictive control of battery systems for frequency regulation markets using physics-based models Y Cao, SB Lee, VR Subramanian, VM Zavala Journal of Process Control 90, 46-55, 2020 | 23 | 2020 |
| Scalable modeling and solution of stochastic multiobjective optimization problems Y Cao, LF Fuentes-Cortes, S Chen, VM Zavala Computers & Chemical Engineering 99, 185-197, 2017 | 22 | 2017 |
| A scalable global optimization algorithm for stochastic nonlinear programs Y Cao, VM Zavala Journal of Global Optimization 75 (2), 393-416, 2019 | 21 | 2019 |
| Time-variant digital twin modeling through the Kalman-generalized sparse identification of nonlinear dynamics J Wang, J Moreira, Y Cao, B Gopaluni 2022 American Control Conference (ACC), 5217-5222, 2022 | 20 | 2022 |
| Supply reliability assessment of a gas pipeline network under stochastic demands Q Chen, L Zuo, C Wu, Y Cao, Y Bu, F Chen, R Sadiq Reliability Engineering & System Safety 209, 107482, 2021 | 19 | 2021 |
| A sigmoidal approximation for chance-constrained nonlinear programs Y Cao, VM Zavala arXiv preprint arXiv:2004.02402, 2020 | 18 | 2020 |
| Exergy analysis and optimisation of an industrial-scale circulation counter-flow paddy drying process C Li, Y Chen, X Zhang, G Mozafari, Z Fang, Y Cao, C Li Energy 251, 123901, 2022 | 16 | 2022 |
| Using stochastic programming to train neural network approximation of nonlinear MPC laws Y Li, K Hua, Y Cao Automatica 146, 110665, 2022 | 15 | 2022 |
