About
Hi, I’m Hossein
I’m a PhD researcher at the University of Alberta working on machine learning–based modeling and control for hydrogen-assisted engines and energy systems. My work bridges control theory (MPC/NMPC) and data-driven modeling (deep learning, system identification) with a strong focus on real-time deployment, safety constraints, and experimental validation.
My goal is to develop reliable control strategies that enable higher hydrogen utilization, lower emissions, and stable combustion under practical operating limits.
Research focus
My research centers on learning-enabled control for complex nonlinear systems, especially combustion and energy applications:
- Machine learning–enhanced NMPC (learning models for prediction + constraint-aware control)
- Real-time, cycle-to-cycle optimization for multi-cylinder combustion stability and homogeneity
- Data-driven & physics-informed modeling (e.g., LSTM-based predictors and hybrid models)
- Safety- and emissions-aware control (stability constraints, abnormal combustion prevention)
- Experimental validation on engine test platforms
Collaboration
I’m interested in collaborating on projects related to:
- Learning-based MPC / safe RL for real systems
- Control-oriented ML modeling (hybrid / physics-informed)
- Energy, engines, and complex nonlinear dynamical systems
If you’d like to connect, please use the Contact page.
CV
You can download my CV here: Download CV