Rate My Professor Mona Faraji Niri

Faraji Niri's research interests center on modelling, control, artificial intelligence, and machine learning for lithium-ion battery systems, including battery manufacturing processes, digital twins, state estimation, thermal management, and performance optimization for electric vehicles and renewable energy storage. Key publications include 'Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence' (Energy & AI, 2022), 'Systematic analysis of the impact of slurry coating on graphite anode quality for Li-ion batteries' (Energy Storage Materials, 2022), 'State of power prediction for lithium-ion batteries in electric vehicles via wavelet-Markov load analysis' (Journal of Power Sources, 2020), 'A Review of the Applications of Explainable Machine Learning for Lithium-Ion Batteries: From Production to State and Performance Estimation' (Energies, 2023), and contributions to the 'Roadmap on Li-ion battery manufacturing research' (Journal of Physics: Energy, 2022). Her scholarly output has accumulated over 1,400 citations, with an h-index reflecting significant influence in battery systems engineering. Notable awards encompass the TechWoman100 Award (2021), Royal Academy of Engineering Global Talent endorsement (Future Promise, 2021), and the Faraday Institution Community Award for STEM Outreach and Public Engagement (2025). She engages in public lectures, STEM outreach, and collaborative projects with the Faraday Institution and industrial partners, advancing clean manufacturing for net-zero carbon goals.