AISys 2021

Best papers of the workshop, after further revisions and independent reviews, will be considered for publication in a special issue of a renowned journal. By this holistic view we encounter a variety of challenges along the AI modeling cycle and software system engineering lifecycle as outlined in the figure below such as: • theory-practice gap in machine learning with impact on stability, reproducibility or integrity due to limitations of nowadays theoretical foundations in statistical learning theory or lack of control of high-dimensionality effects of deep learning; • facing computational constraints, e.g. All submissions will be peer-reviewed by, at least, 3 reviewers and judged on the basis of originality, contribution to the field, technical and presentation quality, and relevance to the workshop. Short papers are meant for timely discussion and feedback at the workshop. Papers are accepted with the understanding that at least one author will register for the conference to present the paper.