Conference Proceedings (peer-reviewed)
Publications as an Assistant Professor after joining UT Austin
14. Lee, J., Kutanoglu, E., Baldea, M., and Mitrai, I., 2026, Effect of data center and electrified manufacturing demand on power grid expansion. Accepted CIRP Conference on Manufacturing Systems (CIRP CMS)
13. Agyeman, B.T., Li, Z., Mitrai, I. and Daoutidis, P., 2026. A hybrid reinforcement and self-supervised learning aided benders decomposition algorithm. Accepted at 2026 IFAC World Congress
12. Mitrai, I., 2026, Discovering interpretable piecewise nonlinear model predictive control laws via symbolic decision trees. arXiv preprint arXiv:2510.10411, Accepted at 2026 American Control Conference
11. Nassaji, A., Mitrai, I., and Daoutidis, P., 2026, Approximate dynamic optimization via deep neural operators. Accepted at 2026 American Control Conference
Prior to joining the University of Texas at Austin
10. Lim, J., Mitrai, I., Daoutidis, P., and Stamoulis, C., 2024, Effects of topology on the controllability of brain connectomes through sparsity promoting control. 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1-4. IEEE, 2024. [link]
9. Mitrai, I., Palys, M., and Daoutidis, P., 2024, Optimal transition for ammonia supply chain networks via stochastic programming, Foundations of Computer Aided Process Design (FOCAPD) [link]
8. Mitrai, I., and Daoutidis, P., 2024, Learning to recycle Benders cuts for mixed integer model predictive control, Computer Aided Chemical Engineering, Vol 53, pp. 1663-1668, Elsevier. [link]
7. Mitrai, I., and Daoutidis, P., 2024, Machine Learning-Based Initialization of Generalized Benders Decomposition for Mixed Integer Model Predictive Control, 2024 American Control Conference (ACC), pp 4460-4465, IEEE. [link]
6. Tang, W., Allman, A., Mitrai, I. and Daoutidis, P., 2023, Resolving large-scale control and optimization through network structure analysis and decomposition: A tutorial review. 2023 American Control Conference (ACC) (pp. 3113-3129). IEEE. [link]
5. Mitrai, I., and Daoutidis, P., 2023, A graph classification approach to determine when to decompose optimization problems, Computer Aided Chemical Engineering (Vol. 52, pp. 655-660). Elsevier. [link]
4. Mitrai, I., and Daoutidis, P., 2022, Learning to Initialize Generalized Benders Decomposition via Active Learning, Foundations of Computer Aided Process Operations / Chemical Process Control 2023, San Antonio TX. [link]
3. Mitrai, I. and Daoutidis, P., 2021, An adaptive multi-cut decomposition-based algorithm for integrated closed loop scheduling and control, Computer Aided Chemical Engineering (Vol. 49, pp. 475-480). Elsevier. [link]
2. Mitrai, I., Stamoulis, C., and Daoutidis, P., 2021, May. A sparse H∞ controller synthesis perspective on the reconfiguration of brain networks, 2021 American Control Conference (ACC), pp. 1204-1209. IEEE. [link]
1. Mitrai, I., Tang, W., and Daoutidis, P., Control of core-periphery networks under sparse feedback controllers. In International Conference on Complex Networks & Their Applications, pages 585–587, 2019