Publications, Activities, and Awards
- Transient Modeling of a Solid Oxide Fuel Cell using an Efficient Deep Learning HY-CNN-NARX Paradigm
- 2024 Canadian Hydrogen Convention
- Canadian Hydrogen Convention
- Cold Climate Impact on Air-Pollution-Related Health Outcomes: A Scoping Review
- Control-oriented Modeling of a Solid Oxide Fuel Cell Affected by Redox Cycling using a Novel Deep Learning Approach
- Deep learning based model predictive control for compression ignition engines
- Design, thermodynamic, and economic analyses of a green hydrogen storage concept based on solid oxide electrolyzer/fuel cells and heliostat solar field
- Developing a Time-Efficient Model for Solid Oxide Fuel Cells Using Self-Supervised Convolutional Autoencoder and Stateful LSTM Network
- End-to-End Deep Neural Network Based Nonlinear Model Predictive Control: Experimental Implementation on Diesel Engine Emission Control
- Hybrid emission and combustion modeling of hydrogen fueled engines
- Hybrid Machine Learning Approaches and a Systematic Model Selection Process for Predicting Soot Emissions in Compression Ignition Engines
- Imitative Learning Control of a LSTM-NMPC Controller on PEM Fuel Cell for Computational Cost Reduction
- Integrating Machine Learning and Model Predictive Control for automotive applications: A review and future directions
- Invention disclosure: SOFC diagnostics and control with use of customized power electronics
- Laminar Flame Speed modeling for Low Carbon Fuels using methods of Machine Learning
- Machine Learning Integrated with Model Predictive Control for Imitative Optimal Control of Compression Ignition Engines
- Model Predictive Control of Internal Combustion Engines: A Review and Future Directions
- Modeling and microstructural study of anode-supported solid oxide fuel cells: Experimental and thermodynamic analyses
- Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
- Performance and Emission Investigation of Hydrogen Diesel Dual Fuel Combustion
- Performance Prediction of a Range of Diverse Solid Oxide Fuel Cells using Deep Learning and Principal Component Analysis
- Real-time vehicular fuel consumption estimation using machine learning and on-board diagnostics data
- Safe deep reinforcement learning in diesel engine emission control
- SOFC Database
- Thermodynamic and Economic Analysis of a Novel Concept for Methane Pyrolysis in Molten Salt Combined with Heliostat Solar Field
- Transfer learning-based deep neural network model for performance prediction of hydrogen-fueled solid oxide fuel cells
- Transient NOx emission modeling of a hydrogen-diesel engine using hybrid machine learning methods