| Decomposition of integrated scheduling and dynamic optimization problems using community detection I Mitrai, P Daoutidis Journal of Process Control 90, 63-74, 2020 | 21 | 2020 |
| Stochastic blockmodeling for learning the structure of optimization problems I Mitrai, W Tang, P Daoutidis AIChE Journal 68 (6), e17415, 2022 | 19 | 2022 |
| Renewable hydrogen and ammonia for combined heat and power systems in remote locations: Optimal design and scheduling MJ Palys, I Mitrai, P Daoutidis Optimal Control Applications and Methods 44 (2), 719-738, 2023 | 17 | 2023 |
| A multicut generalized benders decomposition approach for the integration of process operations and dynamic optimization for continuous systems I Mitrai, P Daoutidis Computers & Chemical Engineering 164, 107859, 2022 | 16 | 2022 |
| Efficient solution of enterprise-wide optimization problems using nested stochastic blockmodeling I Mitrai, P Daoutidis Industrial & Engineering Chemistry Research 60 (40), 14476-14494, 2021 | 13 | 2021 |
| Computationally efficient solution of mixed integer model predictive control problems via machine learning aided Benders Decomposition I Mitrai, P Daoutidis Journal of Process Control 137, 103207, 2024 | 7 | 2024 |
| Learning to initialize generalized benders decomposition via active learning I Mitrai, P Daoutidis FOCAPO/CPC, San Antonio, Texas, 2023 | 6 | 2023 |
| Taking the human out of decomposition-based optimization via artificial intelligence, Part II: Learning to initialize I Mitrai, P Daoutidis Computers & Chemical Engineering 186, 108686, 2024 | 5 | 2024 |
| An adaptive multi-cut decomposition based algorithm for integrated closed loop scheduling and control I Mitrai, P Daoutidis Computer Aided Chemical Engineering 49, 475-480, 2022 | 5 | 2022 |
| Taking the human out of decomposition-based optimization via artificial intelligence, Part I: Learning when to decompose I Mitrai, P Daoutidis Computers & Chemical Engineering 186, 108688, 2024 | 4 | 2024 |
| A two-stage stochastic programming approach for the design of renewable ammonia supply chain networks I Mitrai, MJ Palys, P Daoutidis Processes 12 (2), 325, 2024 | 2 | 2024 |
| Resolving large-scale control and optimization through network structure analysis and decomposition: A tutorial review W Tang, A Allman, I Mitrai, P Daoutidis 2023 American Control Conference (ACC), 3113-3129, 2023 | 2 | 2023 |
| Internal control of brain networks via sparse feedback I Mitrai, VO Jones, H Dewantoro, C Stamoulis, P Daoutidis AIChE Journal 69 (4), e18061, 2023 | 2 | 2023 |
| Accelerating process control and optimization via machine learning: A review I Mitrai, P Daoutidis arXiv preprint arXiv:2412.18529, 2024 | 1 | 2024 |
| Learning to Recycle Benders Cuts for Mixed Integer Model Predictive Control I Mitrai, P Daoutidis Computer Aided Chemical Engineering 53, 1663-1668, 2024 | 1 | 2024 |
| A graph classification approach to determine when to decompose optimization problems I Mitrai, P Daoutidis Computer Aided Chemical Engineering 52, 655-660, 2023 | 1 | 2023 |
| A sparse H∞ controller synthesis perspective on the reconfiguration of brain networks I Mitrai, C Stamoulis, P Daoutidis 2021 American Control Conference (ACC), 1204-1209, 2021 | 1 | 2021 |
| 10B: Modeling, Control, and Optimization of Energy Systems II A Allman, I Mitrai 2024 AIChE Annual Meeting, 2024 | | 2024 |
| Data science and analytics for process applications Z Jiang, R Singh, J Na, S Rajagopalan, Y Chen 2024 AIChE Annual Meeting, 2024 | | 2024 |
| Accelerating the Solution of Model Predictive Control Problems Via Machine Learning I Mitrai 2024 AIChE Annual Meeting, 2024 | | 2024 |