Research outputs
2026
A Surrogate-Enhanced Framework for flexible and optimal operational space identification under uncertainty
Kay, S., Zhu, M., Lane, A., Shaw, J., & Zhang, D. (2026). A Surrogate-Enhanced Framework for flexible and optimal operational space identification under uncertainty. CHEMICAL ENGINEERING SCIENCE, 321. doi:10.1016/j.ces.2025.122973
2025
A novel approach to identify optimal and flexible operational spaces for product quality control
Kay, S., Zhu, M., Lane, A., Shaw, J., Martin, P., & Zhang, D. (2025). A novel approach to identify optimal and flexible operational spaces for product quality control. CHEMICAL ENGINEERING SCIENCE, 309. doi:10.1016/j.ces.2025.121429
Global and Preference-Based Optimization with Mixed Variables Using Piecewise Affine Surrogates
Zhu, M., & Bemporad, A. (2025). Global and Preference-Based Optimization with Mixed Variables Using Piecewise Affine Surrogates. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 204(2). doi:10.1007/s10957-024-02596-y
2024
Discrete and mixed-variable experimental design with surrogate-based approach
Zhu, M., Mroz, A., Gui, L., Jelfs, K. E., Bemporad, A., del Rio Chanona, E. A., & Lee, Y. S. (2024). Discrete and mixed-variable experimental design with surrogate-based approach. DIGITAL DISCOVERY, 3(12), 2589-2606. doi:10.1039/d4dd00113c
2023
Multi-Agent Active Learning for Distributed Black-Box Optimization
Cannelli, L., Zhu, M., Farina, F., Bemporad, A., & Piga, D. (2023). Multi-Agent Active Learning for Distributed Black-Box Optimization. IEEE CONTROL SYSTEMS LETTERS, 7, 1488-1493. doi:10.1109/LCSYS.2023.3270347
Specification-Guided Critical Scenario Identification for Automated Driving
Molin, A., Aguilar, E. A., Nickovic, D., Zhu, M., Bemporad, A., & Esen, H. (2023). Specification-Guided Critical Scenario Identification for Automated Driving. In Unknown Book (Vol. 14000, pp. 610-621). doi:10.1007/978-3-031-27481-7_35
2022
C-GLISp: Preference-Based Global Optimization Under Unknown Constraints With Applications to Controller Calibration
Zhu, M., Piga, D., & Bemporad, A. (2022). C-GLISp: Preference-Based Global Optimization Under Unknown Constraints With Applications to Controller Calibration. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 30(5), 2176-2187. doi:10.1109/TCST.2021.3136711
2021
Preference-based MPC calibration
Zhu, M., Bemporad, A., & Piga, D. (2021). Preference-based MPC calibration. In 2021 EUROPEAN CONTROL CONFERENCE (ECC) (pp. 638-645). Retrieved from https://www.webofscience.com/
2020
A General Dynamic Model of a Complete Milk Pasteuriser Unit Subject to Fouling
Zhu, M., Santamaria, F. L., & Macchietto, S. (2020). A General Dynamic Model of a Complete Milk Pasteuriser Unit Subject to Fouling. In Unknown Book (Vol. 48, pp. 247-252). doi:10.1016/B978-0-12-823377-1.50042-2