New contributor interested in ML-ready electrochemical energy-storage data

Hello everyone,

My name is Alper Bingöl. My research background is in supercapacitor electrode materials, electrochemical energy storage, and machine-learning-assisted materials analysis. I have worked on bio-derived and metal-oxide electrode materials, and I am currently developing reproducible ML workflows for energy-storage data, including thermal descriptors, electrochemical performance data, and prediction pipelines.

I recently joined the Battery Data Alliance community because I am very interested in open battery data standards, BDF, and AI-ready data structures for electrochemical energy-storage research.

I would be especially interested in contributing from the perspective of supercapacitor and electrode-material datasets, including CV, GCD, EIS, electrode composition, electrolyte, mass loading, capacitance, energy density, power density, and thermal/TGA-DTG descriptors.

Could you please suggest the best discussion thread or working group for a new contributor with this background?