Tractable Global Solutions to Bayesian Optimal Experiment Design. - Diogo Rodrigues; Georgios Makrygiorgos; Ali Mesbah 002 (CDC, 2020)

Surrogate modeling for fast uncertainty quantification: Application to 2D population balance models. - Georgios Makrygiorgos; Giovanni Maria Maggioni; Ali Mesbah 002 (Comput. Chem. Eng., 2020)

Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks. - Angelo D. Bonzanini; Joel A. Paulson; Georgios Makrygiorgos; Ali Mesbah 002 (Comput. Chem. Eng., 2021)

Scalable Estimation of Invariant Sets for Mixed-Integer Nonlinear Systems using Active Deep Learning. - Angelo D. Bonzanini; Joel A. Paulson; Georgios Makrygiorgos; Ali Mesbah 002 (CDC, 2022)

Performance-oriented model learning for control via multi-objective Bayesian optimization. - Georgios Makrygiorgos; Angelo D. Bonzanini; Victor Miller; Ali Mesbah 002 (Comput. Chem. Eng., 2022)

Towards Personalized Plasma Medicine via Data-Efficient Adaptation of Fast Deep Learning-based MPC Policies. - Kimberly J. Chan; Georgios Makrygiorgos; Ali Mesbah 002 (ACC, 2023)

No-Regret Bayesian Optimization with Gradients Using Local Optimality-Based Constraints: Application to Closed-Loop Policy Search. - Georgios Makrygiorgos; Joel A. Paulson; Ali Mesbah 002 (CDC, 2023)

Lyapunov Neural ODE Feedback Control Policies. - Joshua Hang Sai Ip; Georgios Makrygiorgos; Ali Mesbah 002 (CoRR, 2024)

Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks. - Georgios Makrygiorgos; Joshua Hang Sai Ip; Ali Mesbah 002 (CoRR, 2025)