Dr.-Ing. Joachim Schaeffer
Arbeitsgebiet(e)
Interpretable machine learning, lithium-ion batteries, features, Gaussian processes, field data, Bayesian optimization, hybrid modeling
Kontakt
ccps@iat.tu-...
My research is at the intersection of interpretable machine learning and lithium-ion batteries.
I’m developing robust and interpretable methods to predict cycle life from early test or formation data. Furthermore, I work on the application of Gaussian processes for battery fault detection and prediction from field data.
I care about open source, open data and open science.
