Approach for class-incremental Novel Class Discovery preventing forgetting of past information about the base classes by jointly exploiting base class feature prototypes and feature-level knowledge distillation. Propose a self-training clustering strategy that simultaneously clusters novel categories and trains a joint classifier for both the base and novel classes. This makes the method able to operate in a class-incremental setting.