Battery RUL Prediction
Data-driven Remaining Useful Life (RUL) model for lithium-ion packs. Pipeline from raw signals → features → model → deployment.
About
Engineer by training, writer by habit. I solve practical engineering problems with a taste for theory and a tendency to ask inconvenient questions.
My sweet spot: systems where electronics, control logic, and data meet — battery diagnostics, power converters, energy management, and ML applied to physical systems.
QualificationB.Eng (Electrical) — University of Pretoria
Current focusBattery RUL prediction, embedded power electronics, ML model deployment
ToolsPython, NumPy, scikit-learn, PyTorch, MATLAB, LTspice, Git
InterestPhilosophy of AI, systems design, technical storytelling
If you want the short version: I build things that measure, predict, and control. If you want the long version: follow my blog or message me.
Skills & Expertise
Electrical Engineering
80% university degree ; used in 7+ projects
Writing & Communication
75% — regular weekly writing, teaching experience
Systems & Analysis
80% — cross-disciplinary systems work
Machine Learning & AI
50% — actively learning deep learning & deployment
Featured Projects
Go-kart Energy System
Power electronics, custom BMS and energy distribution to improve efficiency and endurance in racing conditions.
Weekly Tech & Philosophy Blog
A hybrid feed alternating technical deep dives and philosophical reflections on tech and society.
Let's Connect
Interested in collaborating or hiring? I prefer concise messages that state scope, timeline and the key deliverable. If you want a fast response include a few bullet points about the project.
Or drop a quick note: fannyfushayi75@gmail.com