Hossein Mehnatkesh
PhD Researcher | Machine Learning & Model Predictive Control for Hydrogen-Fueled Engines
I develop machine learning–enhanced nonlinear model predictive control methods for real-time combustion optimization, emissions reduction, and safety in hydrogen-assisted energy systems at the University of Alberta.
- ML-enhanced NMPC and real-time control
- Hydrogen–diesel dual-fuel engines
- Data-driven and physics-informed modeling
- Cycle-to-cycle combustion optimization
- Experimental validation on multi-cylinder engines
This site is intended for researchers, collaborators, and industry partners interested in ML-based control and energy systems.
Research Focus
Learning-based NMPC, safe constraint handling, and real-time deployment for hydrogen-assisted combustion systems.
See projects →Publications
Papers on predictive control, ML modeling, and experimental validation in engine systems.
Browse publications →Open-source & Code
Reproducible tooling for data processing, model training, and MPC/RL experimentation.
GitHub profile →