Shehzar Shahzad Sheikh is a PhD researcher in Battery Systems Engineering at Cranfield University, working under the supervision of Professor Daniel J. Auger. He has a background in electrical engineering, battery diagnostics, and machine‑learning‑based estimation for energy‑storage systems. His research focuses on developing advanced state‑of‑health estimation, fast model‑calibration techniques, and electrochemical‑data‑driven diagnostic methods for real‑time battery management. By integrating laboratory experimentation, large‑scale data analysis, and control‑oriented modelling, he aims to develop reliable diagnostic and prognostic tools suitable for next‑generation applications in sustainable mobility, aerospace platforms, and intelligent power systems.

Shehzar is currently working on machine‑learning‑supported battery health estimation, impedance‑spectroscopy‑based diagnostic modelling, physics‑informed characterisation, and hybrid prognostic approaches for predicting battery ageing and remaining useful life. His previous research at NUST—conducted in collaboration with Arizona State University—resulted in multiple peer‑reviewed publications on lithium‑ion degradation modelling, microgrid analysis, and sustainable energy systems. Before joining Cranfield, he served as an Engineering Officer and Quality Assurance Officer in the Pakistan Air Force, managing high‑reliability electrical and avionics systems and leading technical teams in demanding operational environments. He is a Senior Member of IEEE and a qualified Professional Electrical Power Engineer, bringing more than seven years of combined research and engineering experience to emerging challenges in battery technology, aviation electrification, and smart power infrastructures.