State estimation
Nonlinear and hybrid observers for systems with non-monotonic measurements, including battery state-of-charge estimation and hysteresis modelling.
Modelling · Estimation · Control
I develop models and estimation methods for energy systems, with a focus on battery degradation, condition monitoring and safe operation.
My work connects physical models, measurements and operating decisions. I study what can be inferred about a system's internal state, and how that information can support its operation over time.
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Nonlinear and hybrid observers for systems with non-monotonic measurements, including battery state-of-charge estimation and hysteresis modelling.
Physics-based battery degradation models, mechanism-level health assessment and the effects of operating decisions on future performance.
Observability analysis, experiment design and sensor placement, together with fault diagnosis for battery cells and packs.
2026 to present
Postdoctoral Researcher · Electrical Engineering
2022 to 2026
Postdoctoral Research Fellow · Mechanical Engineering
2017 to 2022
Ph.D. in Mechanical Engineering