ASSIST research addresses the following key aspects in the software engineering process of AI-based systems:

1. Research in automation techniques for data cleaning and pre-processing, in order to support pre-modelling stages in handling and transforming the datasets for them to be ready to be used by machine learning (ML)-based predictive models.

2. Research in automating the process of exploratory analysis of data, a key phase in data science, by means of statistical and graphic means to support understanding and data value acquisition.

3. Research in a catalogue of predictive models based on ML algorithms aiming to solve a number of different problems with the aid of automated AI put at the disposal of non-expert users.

4. Research in hyperparameters optimisation techniques towards democratising the use of regression and classification models leading to optimal results without human interventions.