Deep in tinkering with AI tools, chasing fresh ideas, and building new things with Python.
By day, I'm a battery engineer with a PhD, working on motorsport battery systems — where Matlab/Simulink/Python is my daily tool. Outside of work, I'm deep in learning new tricks, like using A.I. and developing some new projects.
It's never too late to learn AI: "The best time to plant a tree was 30 years ago. The next best time is now."
This website is my personal space to record my AI journey, share resources, and document my learning experiences. I'll keep exploring, building, and sharing it all here.
Battery Related Work
Experience
Featured Projects
End-to-end pipeline for chaotic race telemetry. Preserves electrochemical features needed for failure prediction.
Scaled cell-level physics models to full pack simulations for eVTOLs. Matched real-world flight data with <2°C error.
IC/DV analysis and ML clustering to identify degradation modes. Automated processing of 50+ data channels.
Education
Key Publications
- 2019 "Data-driven health diagnostics and lifetime prognostics for lithium ion battery: a review" — Renewable & Sustainable Energy Reviews
- 2018 "Random forest regression for online capacity estimation of lithium-ion batteries" — Applied Energy
- 2018 "A quick on-line state of health estimation method for Li-ion battery with incremental capacity curves" — Journal of Power Sources