RSS: Data Science and Artificial Intelligence provides a new forum for research of interest to a broad readership spanning the data science fields. Created in recognition of the growing importance of data science and artificial intelligence in science and society, the new journal aims to fill the need for a venue that truly spans the relevant fields.
This new open access journal joins the RSS family of world class statistics journals and is published by Oxford University Press.
Scope and type of papers
RSS: Data Science and Artificial Intelligence is seeking high quality papers from across the breadth of these disciplines which encompass statistics, machine learning, deep learning, econometrics, bioinformatics, engineering, computational social sciences, and beyond.
As well as three primary paper types - method papers, applications papers and behind-the-scenes papers - RSS: Data Science and Artificial Intelligence will publish editorials, op-eds, interviews, and reviews/perspectives in line with its goal to become a primary destination for data scientists
Why Publish?
RSS: Data Science and Artificial Intelligence offers an exciting open access venue for your work with a broad reach and is peer reviewed by editors esteemed in their field. Discover more about why the new journal is the ideal platform for showcasing your research
Submit a paper
Find out how to prepare your manuscript for submission and visit our submission site to submit your paper
Editors
Sach Mukherjee is Director of Research in Machine Learning for Biomedicine at the Medical Research Council (MRC) Biostatistics Unit, University of Cambridge, and Head of Statistics and Machine Learning at the German Center for Neurodegenerative Diseases.
Silvia Chiappa is a Research Scientist at Google DeepMind London, where she leads the Causal Intelligence team, and Honorary Professor at the Computer Science Department of University College London.
Neil Lawrenece is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge. He has been working on machine learning models for over 20 years. He recently returned to academia after three years as Director of Machine Learning at Amazon.
View the full editorial board here: Editorial Board | RSS Data Science | Oxford Academic (oup.com)
Open Access
RSS: Data Science and Artificial Intelligence is fully open access (OA) and is published by Oxford University Press (OUP). Your research will be free to read and can be accessed globally. An OA license increases the visibility of your research and creates more opportunities for fellow researchers to read, share, cite, and build upon your findings.
The cost of publishing Open Access may be covered under a Read and Publish agreement between OUP and the corresponding author’s institution. Find out if your institution is participating. Members of the Royal Statistical Society can submit papers at a reduced cost.
Explore the journal’s website now www.academic.oup.com/rssdat
- Copyright and licence
- © 2023 Royal Statistical Society
This article is licensed under a Creative Commons Attribution (CC BY 4.0) International licence.
