IOP Publishing has launched AI Horizons, a new diamond open-access journal devoted to artificial intelligence research for engineering and science, responding to growing demand for work that applies AI to scientific problems rather than treating it as a narrow computing specialty.
The journal is published in partnership with the Eastern Institute of Technology (EIT) in Ningbo, the Zhejiang Association for Science and Technology and the World Association of Young Scientists. Shiyi Chen, president of EIT, serves as editor-in-chief. Chen has worked at Johns Hopkins University in the US, Peking University and the Southern University of Science and Technology, and his research has centered on turbulence and computational fluid dynamics before extending more recently to AI for engineering and industrial applications.
In remarks on the launch, Chen said AI is changing how researchers work with data and develop scientific models, helping them identify patterns and explore problems that are difficult to tackle with conventional methods alone. The scientific value, he stressed, depends on what is learned from the results and how well they hold up to testing. The most promising work, in his view, combines AI with physical understanding and careful comparison against experiments or observations.
Chen said AI for engineering and industrial applications interests him most, particularly turbulence and complex flows. Turbulence has been central to his research for years and is a demanding test for AI because it involves interactions across a wide range of scales. He is interested in how AI can work with physical models to improve simulations and make them more useful in engineering design, and in integrating that work into computer-aided engineering and industrial software so engineers can evaluate designs more efficiently.
The journal's scope brings together AI for science and engineering, spatiotemporal intelligence, embodied AI and quantum intelligence. Chen said he would be particularly interested in papers that use AI to resolve a difficult scientific question or make a previously impractical engineering calculation feasible, while fundamental advances in AI methods are also welcome. Authors are expected to explain what their work makes possible and provide convincing evidence for their claims, including where a method reaches its limits.
Bringing disciplines together will require reviewers who understand both the AI methods and the scientific problem at hand, Chen said, and the journal will seek that combination of expertise in peer review. It also plans to commission reviews and perspectives that help readers understand useful ideas from other fields, with the aim of making papers accessible and valuable beyond their immediate specialty.
Chen said the diamond open-access model matters a great deal. Readers can access papers freely and authors pay no article processing charges because the journal's sponsors cover publication costs, which he said is particularly valuable for researchers with limited funding. He wants the decision to submit to depend on whether the journal is right for the work, without publication costs becoming an obstacle.
On publishing innovation, Chen said many AI studies require readers to have access to code, data and details of model training to assess results properly. Papers should make it easier to reproduce work and test it in other settings, and he would like the journal to explore formats that support this, including interactive material that helps readers examine results. Updates to published work would need clear versioning and appropriate editorial oversight.
Balancing speed with rigor is another priority. Chen said authors deserve timely decisions and useful feedback, and the journal will aim to keep editorial handling efficient and involve suitable reviewers early while giving reviewers enough time to assess the work and authors enough time to address substantive questions.
Looking ahead, Chen said he hopes AI Horizons becomes a journal researchers trust for sound, original work and turn to for ideas they can use in their own fields. He would be especially pleased to see papers published there lead to collaborations between AI researchers and scientists or engineers working on difficult problems, with the journal earning its reputation through the quality of its papers and how well it serves those researchers.
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