Welcome.
I'm Nick — I build computational models, digital twins and mix records. Currently building at EF.
First-class honours from Imperial — departmental prize for best performance in physical chemistry, Dean's List every year, and best MSci project in physical chemistry at MIT. The only student from my year selected for the MIT exchange program.
If you take nothing else away from this page, I hope you discover at least one tune you enjoy.
Listening
Listening history →Writing
Opinion: OpinionsMar 2026+
Why do strong opinions matter when founding an important company?
Open in Substack →Projects
Zero-Dimensional Digital Twin for Redox Flow BatteriesHigh-fidelity stack-scale RFB simulation generalised for any redox chemistry. Simulates days of cycling in seconds.Digital TwinRedox Flow BatteriesPhysics-Informed ModellingPython+
Developed during my master's at MIT (Brushett Lab). Presents a zero-dimensional model generalised for any redox chemistry and operating conditions — capable of simulating stack-scale cycling at high fidelity in seconds. Enables fast design iteration and real-time control applications. Awarded best MSci project in physical chemistry at Imperial. Published in the Journal of The Electrochemical Society (Q1).
Gaussian Process Inference of Li-ion Thermal Runaway KineticsSurrogate model that extracts failure dynamics from sparse, noisy experimental data — making physically unobservable states predictable.Gaussian ProcessesThermal RunawayLi-ion BatteriesSurrogate Modelling+
Built during a research placement at the Faraday Institution. Uses Gaussian Processes to infer electrolyte decomposition reaction networks from sparse concentration profile data. Latin Hypercube Sampling generates candidate frequency factor sets; the GP surrogate inverts this to estimate kinetic parameters from real experimental data. Robust parameter optimisation via continuous rank probability score. Published in Computer Aided Chemical Engineering.
Dual-server AI architecture for a portfolio management team. Design to production in two months.
Early hire at an AI-native energy storage startup. Built and shipped production digital twins for battery cells and packs.
Built a Python/Dash dashboard for lab cycling data visualisation, used across active experiments.
Gaussian Process surrogate model for Li-ion thermal runaway. Published in Computer Aided Chemical Engineering.
PV module test data analysis; industry trend graphics published on the PVEL blog.