We use cookies to improve your website experience. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. By closing this message, you are consenting to our use of cookies.

Connection Science

Now An Open Access Journal

Submit your research

Connection Science is converting to Open Access from its 2022 volume

Connection Science focuses on aspects of Computer Science which explore the convergence of analytic and synthetic sciences, including artificial intelligence and neuroscience. 

It plans to foster the immediate and widescale dissemination of research results through adoption of an  Open Access (OA) model.  Every  submission will continue to be subject to the usual vigorous reviewing process, and to help with this process, the journal as a strong editorial board of prominent and respected academics from a diverse regional and institutional background. 

As part of this transition, all manuscripts received going forward will proceed through Connection Science’s new Open Access submission portal. Authors who submit after 11th May 2021 will be required to pay an article publishing charge (APC) which can be covered by an author’s funder or institution.

Contribute to Connection Science’s content

Interested authors should visit the Taylor & Francis Open Access Members and  Open Access Agreements pages in case they are based at an institution that may have funds available to authors wishing to publish in  Connection Science. Interested readers may also want to consider signing up to receive  latest article alerts to keep up-to-date with the latest research published in the Journal

We look forward to receiving your submissions and hope you join us to embrace  Connection Science’s Open Access future. 

Connection Science  is particularly interested in receiving manuscripts arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.  

There is a comprehensive description of the journal scope as well as a clear set of instructions for authors in the  journal website.  


“The publisher and editors have taken every step to ensure that Author Processing Charges (APCs) associated with Open Access publication do not become a prohibiting factor for publication of high-quality papers through introduction of a very competitive pricing scheme as well as setting up a APC discount or waiver initiative.”

Kuan Ching-Li, Editor-in-Chief

Connection Science Editor in Chief Kuan-Ching Li

Why publish open access?

  • Increase the visibility and readership of your research by publishing in a fully open access journal.

  • Make an impact beyond the academy by making your article accessible to anyone, anywhere (including readers in industry and even policy-makers).

  • Benefit from format-free submission, saving you more time for your research.

  • Freely share your work with no restrictions or paywall.

  • Retain ownership of your research through our unrestrictive publishing agreements.

  • Discounts and waivers for researchers in developing countries are available. The journal will also consider requests for discretionary APC waivers. Find out if your institution or country has an open access agreement to publish with us.

Connection Science Journal

Q&A with Professor Kuan Ching-Li

Professor Kuan Ching-Li talks to us about the future of the journal as it progresses to open access, how the journal helps authors to make an impact with their research, and how the journal can help academic and industrial leaders achieve common goals.

Read the latest research

Navigate the links below to read a selection of popular recent open access articles from the journal for free.
Article Author(s)
Sexbots: a case for artificial ethical agents Christopher James Headleand, William J. Teahan & Llyr ap Cenydd
Experience evaluations for human–computer co-creative processes – planning and conducting an evaluation in practice Anna Kantosalo & Sirpa Riihiaho
Learning from data streams and class imbalance Shuo Wang, Leandro L. Minku, Nitesh Chawla & Xin Yao
Evolutionary computation for bottom-up hypothesis generation on emotion and communication Casper Hesp, Bram T. Heerebout & R. Hans Phaf
Find the latest tweets from @tandfonline

We use cookies to improve your website experience. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. By closing this message, you are consenting to our use of cookies.