BIOSKETCH

I am a Ph.D. candidate in Mechanical Engineering at the University of Alberta specializing in machine learning, prognostics, and physics-informed modeling for advanced energy systems, with applications in batteries and hydrogen fuel cells. My research focuses on state-of-health (SOH) estimation, remaining useful life (RUL) prediction, degradation diagnostics, and techno-economic analysis for energy storage systems operating under real-world conditions.

My work combines electrochemical knowledge with advanced machine learning techniques to develop scalable and interpretable predictive maintenance frameworks. I developed a physics-informed health monitoring framework for real-time SOH estimation using impedance-derived features and graph-based temporal learning models, enabling accurate degradation tracking and improved interpretability of underlying electrochemical processes. Building on this, I developed probabilistic prognostics frameworks for long-horizon SOH forecasting and RUL estimation, incorporating uncertainty quantification to capture both operational variability and model uncertainty in degradation predictions.

In parallel, I developed diagnostic frameworks for identifying degradation mechanisms using impedance spectroscopy and machine learning classification methods, enabling mechanism-aware fault identification across multiple degradation scenarios. To further improve robustness and computational efficiency, I proposed unified multi-task learning approaches that integrate diagnostics and prognostics into a single framework by conditioning lifetime prediction on degradation mechanism information.

Alongside predictive health monitoring, I have conducted degradation-aware techno-economic and feasibility analysis for energy systems, incorporating lifecycle, performance, and operational trade-offs into system sizing and optimization decisions. My research is conducted in collaboration with Cummins Inc., where I work closely with both battery and fuel cell teams to align modeling approaches with practical implementation constraints, operational requirements, and industrial applications.

I hold an M.Sc. in Mechatronics Engineering and a B.Sc. in Aerospace Engineering, with additional experience in control systems, real-time simulation, and hardware-in-the-loop applications. Through this interdisciplinary background, I aim to develop practical, data-driven solutions that improve the reliability, efficiency, and long-term sustainability of next-generation energy systems.

(May, 2026)